MARTRANS VIRTUAL TRANSPORT CHAIN - Model Design
PORTEL Servicios Telemáticos
EUROPEAN COMMISSION - DGVII "TRANSPORT"
________
EUROMAR EEIG
MARTRANS TASK 2
VIRTUAL TRANSPORT CHAIN
MODEL DESIGN
Identifier :
MARTRANS TASK2 MODEL DESIGN
Version :
2.1
Version Date :
30 JUL 1997
Status :
FINAL
Distribution :
CONFIDENTIAL
Abstract :
THIS DOCUMENT CONTAINS THE MODEL DESIGN
OF THE VTC FOR MARTRANS TASK 2: VIRTUAL
TRANSPORT CHAIN
© 1997 PORTEL Servicios Telemáticos
Task 2 Model Design ver 2.1
30 Jul 1997
No part of this document may be reproduced, distributed or disclosed without the prior written consent of PORTEL Sistemas Telemáticos except for the purpose
to which it is explicitly produced
MARTRANS VIRTUAL TRANSPORT CHAIN - Model Design
PORTEL Servicios Telemáticos
QUALITY CONTROL
MARTRANS
Originator(s)
Rafael Peña
Visa and Date:
Appraisal authority:
Sergio Acebo
Task Leader for Task 2
Visa and Date:
Appraisal authority:
Alvaro J. García
MARTRANS QA
Visa and Date:
Appraisal Authority
Ramón Gómez Ferrer
Visa and Date:
Appraisal Authority
Visa and Date:
Task 2 Model Design ver 2.1 — 30 Jul 97
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VERSION HISTORY
Version Date
creation
of
Status
Author
1.0
08/05/97
Draft
Rafael Peña
2.0
30/06/97
Final
Rafael Peña
2.1
30/07/97
Final
Rafael Peña
Changes/Comments
DISTRIBUTION LIST
Recipient
Company/Function
Ramon Gomez-Ferrer
IPEC/MARTRANS Programme Officer
Sergio Acebo
PORTEL/Martrans Task Leader for Task 2
Alvaro J. García Tejedor
PORTEL/Martrans QA
Elio B. Cereghino
EUROMAR/Manager
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TABLE OF CONTENTS
1. INTRODUCTION
4
1.1 SCOPE
1.2 DOCUMENT STRUCTURE
1.3 REFERENCE AND APLICABLE DOCUMENTS
1.4 DEFINITIONS AND ACRONYMS
4
5
5
6
2. MODEL DESIGN
7
2.1.
2.2.
2.3.
2.4.
OBJECTS
RELATIONSHIPS.
RULES.
EVENTS.
8
12
16
23
3. TYPE OF MODELS.
27
4. SCALABILITY.
31
5. VTC API.
33
6. ANALYSIS OF DEVELOPMENT TOOLS.
34
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1.
MARTRANS VIRTUAL TRANSPORT CHAIN - Model Design
INTRODUCTION
1.1 SCOPE
This document follows the basic design ideas pointed out in the Model Design (Draft) document.
Obviously, these ideas have been improved due to a more detailed analysis of real processes
producing a different methodological deployment.
The contribution of applied real systems conceptual analysis to a practical case (Martrans Task 2.
Virtual Transport Chain. Functional Specifications and User Requirement), where different
transport means are being analyzed and the goods flow along with the associated document flows,
shows the importance of the simulation as a tool to compare the benefits that EDI would provide
as an alternative information system as to those currently existing. All those details and nuances
have contributed to improve the model design allowing us to overcome any virtual transport chain
to any degree of detail or generality needed, where the educational aspect, among others, is
perfectly comprised.
The basic structure remains as the one in the previous document where the virtual transport chain
is represented as a graph. This new vision's biggest improvement is the richness of all the content
design elements: nodes, connections, rules and events; where all the necessary requirements
have been checked to jointly represent several transport chains and different types of goods in the
same competitive simulation.
The main differences from one vision to the other are that the delay phenomenon does not need to
be explicitly specified but handled by the system as a natural result of the simulation process. An
availability schedule of nodes and connections is included in order to correctly represent the
situations caused by warehouse timetables, working turns, port closure, departure/arrival transport
timetables (sea lines, goods trains, etc.) and even the strikes or catastrophes (understood as the
lack of a resource, for instance, a shipwreck, an airport temporal closure)
The user interface (VTC API) remains unchanged from the previous version because its logical
statement is not affected by the greater precision of the logical design. More detail will be achieved
in the development phase.
The current document stays as the logical model design understood as a true methodology ready
to design a virtual transport chain, and how (the order) we must work with the different system
elements to achieve a goods traffic simulation along the time and through a given design.
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1.2 DOCUMENT STRUCTURE
Chapter one introduces the document and references other documents needed for its generation.
It details the acronyms and references introduced in its content.
Chapter two contains the model design of the virtual transport chains. An introduction about the
used modeling methodology is done and each one of the design elements is detailed: Objects,
Relations, Rules and Events.
Chapter three contains a description of some of types of model that can be made about Virtual
Transport Chains, giving an idea about the type of results and analysis that could be made.
Transactional, Stochastic, Optimal and Scenario (What happens if ...?) models are studied
particularly.
Chapter four introduces the concept of model scalability until the current design limit allows from a
higher level of detail to one with a big complexity on users and elements. A potential upgrade is
foreseen in the future.
Chapter five contains a brief and general description about the user interface with the needed
functionalities to define, upgrade and execute the simulation models.
1.3 REFERENCE AND APLICABLE DOCUMENTS
[FSUR]
Martrans. Task 2. Virtual Transport Chain. Functional Specifications and User
Requirements.
[MDD]
Martrans. Task 2. Virtual Transport Chain. Model Design (draft).
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1.4 DEFINITIONS AND ACRONYMS
MARTRANS
VTC
Virtual Transport Chain
DAG
Direct Acyclic Graph
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2. MODEL DESIGN
The conceptual model, with a partial aspect of reality, holds a list of elements and relationships
that, conveniently set, permit to obtain an abstract system representing that reality (see Figure 1).
The manipulation of a model is much easier and more immediate than the manipulation of the real
objets. That is the reason why they are tools of an enormous usefulness when simulating the
behavior of a real system, predicting its future evolution or analyzing how it will behave at different
possible situations. The simulation allows us to create new situations without directly controlling
the nature of the real system. Building a water dam, designing a road, enabling a new sea line, or
building new warehouses means years of work for a sometimes-hazardous result. Thanks to the
models all these hard jobs just need some few hours to carefully check the advantages or
disadvantages of one or some other choice allowing the creation of much cleaner and adjusted-toour-needs strategies of real operation.
MODELLING
CONCEPTUAL
MODEL
tion
Abstrac
Verify
Modelling
Con
Revision
tras
Ref
inin
t
g
REAL
PROCESS
SIMULATION
MODEL
Figure 2.1. Modeling process
In fact, no model exactly adjusts to the real phenomenon it is trying to represent, but it is also true
that models can be created with enough detail and precision to be useful to our purposes. The
scientific process for its elaboration and successive depuration comparing the model with the
reality assure us the continuous improvement till the limit of current technology. Though they are
no completely exact, they allow us to evaluate the error margins with those that really operate and
thus to keep a constant reference with the real world. On the other side, many of the aspects of
the simulation is the choice of alternatives, and though the model is not exact in an absolute scale,
it can be much more exact in terms of comparison among different scenarios.
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MARTRANS VIRTUAL TRANSPORT CHAIN - Model Design
This conceptual system must be able to manage not just the transport flows but also the related
document flows. The importance of document systems in transport chains can be a crucial aspect
in some precise phases of goods transport. The comparative study of models in a same transport
chain under different aspects of document management (EDI vs. current systems) can provide a
general rule of coherent politics aimed to improve the transport systems.
Finally, the last important test that must pass any interesting model is that all the elements of its
conceptual model must be enough to correctly represent the real aspects considered so by the
researcher. Further than this first consideration, the building of the model, using conceptual
elements as parts of a system whose refinement process, in contrast with reality, will assure us a
better representation of the real world, only if the most adequate conceptual model has been built.
The elements that are usually contained in all conceptual models can be grouped into four
categories:
Objects. They are the representation of physical or abstract elements
(personal or legal entities) that participate in the real process.
Relationships: They define the processes interacted among objects.
Rules: They define how the processes are established between
several objects and there are some conditions or limitations to them.
Events: They are the incidents and/or external actions that interact
with the system (for instance, the prediction of goods arrivals in the
port) and any other action that can have an influence on the process
(permissions, authorizations, transport timetables, able warehouses,
transport means, etc.).
The first two elements (objects and relationships) are described with attributes that define their
characteristics and functioning.
In the virtual transport chain, the central process is the goods transport from end to end, that is
why the conceptual model is aimed to describe with the greater possible precision such
phenomenon as it happens in the real world.
2.1. OBJECTS
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They are represented with a circle and they will indicate the state or
situation in which a goods is set at a given moment of the virtual transport
chain (VTC).
In a general way, the object is identified with a warehouse, real or fictitious, where the goods is
placed. From now on, it will be given the name of node.
Given that transport chains move several types of different goods, the object attributes will be
applied to every goods that will be represented simultaneously. Except some attributes
(identification and total storage node), the others will be applied by goods type:
 Identification: This attribute establishes a unique name which will identify the
node in case of simulation.
 Maximum size of storage:. This attribute will be used to establish three
typologies according to its value.
0
Not ready storage. Warehouses can not be ready to hold some type of
goods (for example, a warehouse in open air can not be used to keep
frozen bulk goods).
When a simultaneous simulation of several types of goods is being
done, it can be used to separate, on the global transport circuit, which
are the routes that can use each one of them.
A
Limited available storage to a quantity A. Almost all elements of the
transport chain (warehouses, docks, ships, trains, trucks, etc.) have a
limited capacity of storage. This maximum limit is set by the quantity A.

Unlimited available storage: There is no limitation on the goods
quantity that the object can store. The generic inputs and outputs of the
simulation system can be considered, for example, unlimited
warehouses from where the goods dynamically flows (sources) or where
all the resulting goods finish the process (sinks). To improve the
understanding of the simulation model diagrams, this type of node will
be denoted with an square sign.
 Stored units. It indicates how many goods are being stored in a given node at
a give time. The stored goods must be less or equal than its maximum capacity
of storage.
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 Measure units. It denotes in what units have been expressed the previous
attributes. The measure units will depend upon the considered goods type.
Some of the most common ones are:
Tm
Metric tons. Used for solid bulks.
m3
Cubic meters. Used for liquid chemical products or liquid gases.
TEU
20
feet
standard
container.
Used
for
external
homogeneous/heterogeneous goods packing. There also exists
refrigerator-containers with the same format. Containers of other
formats are assimilated to the standard container units (½ TEU, 1½
TEU, 2 TEU, etc.).
Pallet Fruits and grocery packing for refrigerated transport. The product
goes inside the Pallet in wood or carton boxes. For example, a fruit
pallet can weight 1 Tm aprox. (about twenty pallets per refrigerated
truck).
There will exist unit conversion tables depending on the type of goods to
homogenize, for instance, total storage in a node of all the goods (see next
attribute).
 Node's Total Storage. When simulating the concurrent traffic of several goods,
it expresses the total quantity that can be stored as total sum of all the types of
goods that can hold the given node. It only has a sense in case of limited
storage nodes.
This attribute is generic of the node and it will not unfold depending on the type
of goods.
If X1, X2, ... , Xn are the quantities stored of the goods 1, 2, ..., n in a given
node. If A1, A2, ..., An are the quantities that the node can keep of those goods.
And if T is the total storage of a node, the next two conditions must be verified:

The stored quantity of each goods must be less or equal its maximal
limit in the node.
X i  Ai

MARTRANS
 i 1, n 
[2.1.1.]
The stored quantity of all the goods must be less or equal (once all
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the conversions of corresponding units have been made) than the
node's total limit.
n
X
i 1
i
 T
[2.1.2.]
 Node's availability. Transport means (considered as warehouses) that have an
arrival timetable (for example, an air or sea line arrivals), the fact that
warehouses can be opened or closed depending on a workable day or not, etc.,
have as result that in the simulation process such an object is not in situation of
storing goods unless the date and time of the simulation coincides with its
availability period.
The use of a node's availability timetable allows regulating the storage and the
traffic of goods through the node just when it will be operative.
 Mean delay time. When the goods arrives to a node it must wait a certain time
before it can be moved to the next node. This attribute is very useful to include
small processes that we do not want to detail (unloading times, permissions and
authorizations, inspections, etc.).
Given that in the real process the delay time can vary because of very different
causes and circumstances, the attribute has been foreseen to contain all the
parameters of a normal distribution (mean and standard deviation).
 Costs per unit of goods and stored time. The storage generates a cost per
quantity, type of goods and storage time. Prizes can be variable therefore the
attribute has been thought to contain the values of a normal distribution of unit
prizes per goods and unit of time (mean and standard deviation).
 Requirements. In a node, the goods is available to be transferred to the next
node when it has accomplished with its mean delay time. However, the
availability criteria can also depend on some events (some of them or all of
them at the same time). In the case of permissions, certifications, inspections,
etc.
The possibility is given to associate the availability of a type of goods in a node
(besides the average delay time) to the occurrence of such events.
Furthermore, this circumstance is very useful to do a tracking of the transport
process in an educational model, simulating the going of the goods as a
consequence of the direct and concurrent action of the different actors of the
transport chain (customs, shippers, consignees, dockers, etc.) using the
necessary orders and documents.
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2.2. RELATIONSHIPS.
They will be represented by a oriented arrow, with an origin and a
destination, indicating how a goods flow is established between two nodes.
In a generic way, a real or fictitious (for instance, a goods change of status from "stored" to "ready
to load" does not mean a movement but an authorization) transport process is identified, where
the goods moves from one place to another. From now on, this will be given the name of
connection.
The attributes, except for some of them (identification, flow and total flow throughput), are
designed for each type of goods that can circulate through the connection.
 Identification. It is a unique name that will identify the relationship with the
simulation model.
 Flow. It contains the name of the origin node and the destination node to
establish the connection and its orientation. It does not just identify the
connection because several connections are permitted between two nodes.
 Total flow throughput. This attribute is used to establish three types of
connections depending on its value:
0
Unavailable connection. The given goods with a throughput value of
zero can not be transported through that connection.
It is used to separate, in a simultaneous simulation, out of several types
of goods, all the different transport means that can be used in a global
transport schema.
C
Available throughput limited to a quantity C. It indicates the quantity
of goods that can be moved through the connection per time unit.

Unlimited available throughput. There is no limitation on the quantity
of goods that can be moved through the connection. The generic inputs
and outputs of the system, for example, can also be considered as
unlimited flows where dynamically flows the goods of the system
(sources) or where all the resulting goods finish the process (sinks). To
improve the understanding of the simulation model diagrams they will be
noted as block arrow.
For instance, a crane can handle from 60 to 80 Tm per hour and a
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transport strip can have analogous results.
 Measure units. They indicate the units in which the previous attributes are
expressed. The measure units will depend on the considered type of goods
considering the used time unit. The quantity units are the same than those used
in the nodes for the different goods and the time units will be those best
adapted to the real process (days, hours, minutes, etc.).
 Total throughput flow. When simulating the concurrent traffic of several goods
through a limited connection (the stowage resources are limited but, for
example, they are available for any type of goods), it expresses the total
throughput that can be transported as a sum of all the types of goods moved
through that connection.
This attribute is connection-generic and it will not unfold depending on the type
of goods.
If F1, F2, ... , Fn are the goods flows 1, 2, ..., n through a specific connection. If
C1, C2, ..., Cn are the maximum throughputs per goods of the connection. And if
CT is the maximum throughput of the connection, the two following conditions
must apply:

The transported quantity per unit of time for each goods must be less
or equal than its maximum throughput in the connection.
Fi  Ci

 i 1, n
[2.2.1.]
The total transported quantity per unit of time for each goods must be
less or equal (once the necessary unit conversions have been made)
than the total throughput of the connection.
n
F
i 1
i
 CT
[2.2.2.]
 Connection Availability. The worker's schedule, the transport means
breakdowns, and other circumstances make impossible an available goods
transport from one node to another.
The use of an available connection schedule or the effect of external events for
this attribute permits to regulate the goods traffic through a connection just
when it is up.
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 Transport mean time. When the goods is going to be moved from the
connection's origin, the throughput means how much goods will increase the
connection traffic per unit of time. However, its arrival to the destination node
has a transport time through the connection (for example, the ship way from the
origin port to the destination, or the goods way in a transport strip). The attribute
can be used for every type of goods.
Given that in real processes, the transport time can vary for multiple reasons
and circumstances, the attribute has been predicted to contain the parameters
of a normal distribution (mean time and standard deviation)
For example, a truck with 10 Tm capacity can be loaded in about half an hour
(load throughput), however, it can take two days to arrive to destination in a
inter-European route.
 Costs per unit of goods and transport time. The transport generates a cost
per quantity, type of goods and used time. The real costs can be variables, thus
the attribute has been predicted to contain the values of a normal distribution of
unit prizes per goods (mean cost and standard deviation).
 Requirements. When very detailed simulations are being made there can
appear some requirements to set a connection operative. As with the nodes, the
availability depends on the occurrence of a list of events (some or all of them).
A part of the included requirements in the nodes for global type simulations can
be revealed as pertinent for all connections when passing to a more detailed
model (permissions, certifications, work orders, etc.).
Therefore, the possibility is given to relate the availability of each type of goods
to circulate through the connection to the occurrence of these events.
As it has been previously said in the nodes, this possibility is very interesting for
educational simulation purposes or to control and follow all the traffics in a
transport chain.
 Probability. When several connection alternatives exist from a node to one or
more destination nodes, a probability or distribution criteria can be assigned to
each one of them per type of goods. The only condition established is that the
sum of probabilities of all the possible connections, for the same type of goods,
has to be the unit.
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P1
A
Figure 2.2.1. Probability of
P2
B
P3
connection among nodes
C
In the example, three connection alternatives are shown from an origin node to
two destination nodes for given goods. The two first connect nodes A and B and
the third node A with C. If P1, P2 and P3 are the probabilities for each one of
the connections, the following condition must apply:
3
P
i 1
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i
1
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[2.2.3.]
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2.3. RULES.
The system has been prepared to work simultaneously with several types of goods. The following
rules will be applied, when needed, to each one of them.
1) The system updates every clock cycle. The system is initially conceived as a
dynamic system where goods constantly flow through the model. Each clock
cycle the goods situation is completely updated, therefore updating the nodes
(storage) and connection (traffic).
2) External events are treated first of all. Such events will produce the following
actions, among others, during the simulation process:

A clock or frequency of the clock cycles update. Cycles can be regulated
to obtain a bigger or smaller detail of the simulation process.

Model parameters update, for instance, specific requirements fulfillment,
modification of parameters of nodes and connections (limits for storage
and throughput), availability schedules update, readiness or not of a
node or connection, etc.

The establishment of the system's simulation mode (conditioned by the
user, random or optimal).

Goods arrival to the system's entry points. The precise moment and the
detailed treatment are described by the rule 6b.

The simulation, waiting for direct user orders or the definitive cancel of
the simulation.
3) The simulation system update is done backwards, starting on the final terminal
nodes and finishing on the initial nodes. This is so to free storage in the
destination nodes.
4) Each node's update is done depending on each type of goods. The choose of
goods can be done depending on:
MARTRANS

An exploration hierarchy given by the user.

A user's event or direct order.
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
A result of a random choice.

A result of an optimal choice depending on different optimization criteria
(time, costs, or storage).
There are more details in the next section (5h).
5) As the goods has been chosen, the updating process for each node is done
following the next steps:
a - The node's goods is examined and is set as available to be transferred
to the one that verifies some of the next requirements:

It was already set as available.

It was not set as available but it complies with the next two
following conditions:
-
The minimum node delay time has been finished.
-
All needed requirements have been done.
b - Just the available goods can be transferred from that node to the
next(s).
c - The goods can be transferred through the connection if the next two
conditions are fulfilled:

The connection is marked as available.

The destination node has been marked as available.
d - The maximum quantity of goods that can be moved from a node to the
other through a connection is fixed by:
M od  Mín ( MDo , CS x R, ADd )
[2.3.1.]
Where:
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Mod
It is the goods capable of being move from an origin to a
destination node through a specific connection.
MDo
It is the available goods in the origin node o.
CS
It is the remaining throughput of the goods in the given
connection.
R
It is the clock cycle.
CSxR Quantity of goods that can be moved through the connection
using the remaining throughput for that goods.
ADd
It is the remaining storage capacity for the given goods in the
destination node d.
e - The remaining throughput for a goods i in a connection is given by the
following formula:
CS i  Min ( Ci , CT   F j )
[2.3.2.]
j
Where:
CSi
It is the remaining throughput for the goods i of the given
connection.
Ci
It is the maximum throughput for the goods i of the given
connection.
CT
It is the maximum throughput of the connection for all types of
goods.
Fj
It is the flow, which has already been used by other kind of
goods.
The flows F translation to units of goods M is done using the clock cycle
R through the following formula:
M  F xR
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[2.3.3.]
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f - The remaining storage capacity for the goods i in a given node is the
result of the following formula:
DAi  Min ( Ai  X i , T   X j )
[2.3.4.]
j
Where:
DAi
It is the storage availability of the goods i in the give node.
Ai
It is the storage limit of the goods i in the node.
Xi Xj
It is the goods of type i, j stored in a node.
T
It is the global storage capacity for all the node's goods.
g - The transport mean time t from a node to another is verified (if there
isn't, it will be zero, t = 0) and the next criteria is applied:

If the time t is bigger than the clock cycle R (t > R), destination
node's remaining storage capacity is not considered because it is
not possible to foreseen its state several cycles before. The
formula [3.1] is rewritten as follows:
M od  Mín ( MDo , CS x R)
[2.3.5.]
The availability condition in the destination node is also discarded
(rule 5c).
The moved quantity (Mod) will not be effective in the destination
node till the time t has passed.

If the transport time is less than or equal to the clock cycle R (t 
R), the arrival to the destination node of the moved goods
through the connection is updated as results of applying the
formula [2.3.1.].
h - When there exists several transit alternatives from an origin to one or
several destination nodes, the choice of which is the moved goods,
quantity, and the used connection, is done depending on the current
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simulation.

Conditioned to external events. The user is the one who
decides, producing events, how the goods flow is done in that
clock cycle.

Simulated:
-
Probabilistic. Depending on the goods's traffic
probabilities through the different connections. Two
categories are considered:
* Direct. Probabilities
coefficients.
are
used
as
distribution
* Random. It results of the random choice of all the
possible available connections.
-
Optimal. The choice among the available connections
including the possibility to wait in the node (no transport is
done) till the next clock cycle, even if the transport is
possible, is done as a result of a global system
optimization including the following things:
* Minimal transport time.
* Minimal transport costs.
* Storage optimization.
.
Maximize the available storage room for each
type of goods and/or the total (transport as much
as possible from the nodes doing first those
goods saturating the storage).
.
Minimize the storage time.
.
Minimize the storage costs.
i - The process is iterative (a-i) till finishing the possibilities of goods
transport from that node.
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6) The goods arrival to the node is updated.
a - First of all, the node's storage usage rates with the goods arrivals from
other nodes if and only if the transport time t among nodes have been
passed. A goods in standing state (see later) has more priority than the
rest. The quantity that can be stored is limited by the following formula:
M i  Min ( Ai  X i , T   X j )
[2.3.6.]
j
Where:
Mi
It is the goods of type i that can be stored in the node coming
from other nodes.
Ai
It is the storage limit of the goods i in the node.
Xi Xj
It is the goods of type i, j already stored in the node.
T
It is the global store capacity for all the node's goods.
The goods that can not be moved (because of the badly adjusted
connection transport time and the clock ticks) stays in a fictitious and
unlimited warehouse named standing. This fictitious warehouse's goods
are have storage priority on the next clock tick.
b - The goods input is updated from the system inputs when it remains
enough storage capacity for that type of goods depending on the
following formula:
EM i  Min ( Ai  X i , T   X j )
[2.3.7.]
j
Where:
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EMi
It is the incoming goods i in the node coming from the system
inputs.
Ai
It is the storage limit of the goods i in the node.
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Xi Xj
It is the goods of type i, j stored in the node.
T
It is the global storage capacity for all the node's goods.
7) The network nodes are updated on an iterative fashion backwards.
8) The clock is updated to the next cycle.
9) Go to step 1.
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2.4. EVENTS.
They are external actions that control the simulation execution and they are caused by the user or
internal ones generated by the system. Events can be grouped into several categories:
1) Model. They are events that establish/update the simulation model to use. It
defines objects, relationships and attributes. On a defined model, it updates its
design adding or removing objects, relationships and attributes.
For instance, to define a model for the first time it is necessary to use this type
of events to specify its topology in terms of nodes, connections and attributes.
2) Parameters. They are events that initialize/update the attribute values of
objects and relationships.
Parameters are all the attributes that can be updated like capacities (storage
and throughput), times, costs, availability (schedules), and requirements.
3) Clock. They are events that update the clock's date and time or that modify the
simulation cycle.
The model's dynamic update will be done for every clock cycle. Cycles can be
user-regulated in order to have a more or less time detail. Short times mean
simulations close to the continuos process. Longer times make discrete
simulations more and more generic.
4) Transitions. They are events that make a transport from a node to another
mandatory or optional. It can be applied in just one node, a set of them, or the
whole system.
5) Simulation Criteria. They are events that update the simulation criteria:

Conditioned. The user defines through external events how the goods
moves for each clock cycle.

Probabilistic. Depends on the traffic probabilities that have each goods
through the different connections. There are two categories:
- Direct. Probabilities act as a distribution coefficients.
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- Random. Caused by a random choice among the different
available connections. This method is the base for risk analysis in
a transport chain (see later).

Optimal. The choice among the available connections, including the
possibility to wait in the node (no transport is done even if it is possible)
till the next clock cycle, is done as a consequence of a global system
optimization attending things as the following:
- Minimize transport time. The system will tend to move the goods
through the model in order to minimize global transport time.
- Minimize transport costs. The system will tend to move the
goods through the model in order to minimize global transport
costs.
- Optimize storage. The system will tend to move the goods
through the model in order to optimize the global system storage
in the following senses:
* Maximize the available storage room for any type of goods
and/or the total (transport the most of the node's goods
doing first those that are saturating the storage).
* Minimize the storage time.
* Minimize the storage costs.
6) Inputs. They are events that regulate the generic goods inputs to the model.
The system contemplates an incoming rate of goods to any of the model nodes
(not just the origin nodes) in any clock cycle or in accordance to a schedule.
The information can be given with a pre-fixed distribution of quantities or using
a function with a probability distribution in the time.
7) Outputs. They are events that set the type of wanted results, the detail and the
format.
Face to some expectations about general incoming goods in the nodes, it is
able to analyze and store the dynamic evolution (situation for every clock cycle)
of the following information:

Generic system outputs depending on the types of goods and total:
- Quantity.
- Times.
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- Costs.

Nodes depending on the types of goods and total:
-

Stored quantity.
Storage usage rate (%)
Delay times.
Storage costs.
Node's availability (%).
Saturation probability (%). Number of times it has been on the limit
of capacity over the total of situations.
Connections depending on the types of goods and total:
-
Quantity of supported traffic.
Throughput usage rate(%).
Transport times.
Transport costs.
Connection availability (%).
Probability of saturation (%).
The detail means a level of ungrouping or grouping of the resulting information,
in the time as in the model elements (nodes and connections).
The format means as well a mode to present information (numeric or graphic)
as a support (display, file, printer).
The application input expectations to the model in the form of goods units to
transport along the time, gives out several situations: general outputs of
transported units, the situation of a given node and the usage of a connection
between two nodes, as it is shown in the following figure.
As it can be seen in the following figure, the tool to detect bottlenecks (usage =
100%) of nodes and connections is evident.
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Figure 2.4.1.
Model input/output example
8) Scenarios. They are events that establish alternative scenarios to a base
model modifying analysis criteria, system parameter's values, etc. It prepares
the simulation process to show comparative results between the different
scenarios after the analysis in sequence of every one of them.
9) Model management. They are events that allow us to store, restore, and
execute simulation models off-line.
10) Control. They are events used to control the model execution: start, stop,
pause (simple or waiting for user orders), monitoring, etc.
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3. TYPE OF MODELS.
The conceptual system, as it has been designed, can be applied to any virtual transport chain,
ground-based (train or road), air, maritime, as well as any mixed one with all the possible transport
means.
In a design, different types of transport means and/or types of goods can be grouped, even
overlapping nodes and connections, to do a global analysis where the transport means and the
different goods interact in a free or conditioned way.
These are some of the type of models that can be simulated independently of the used transport
structure.
1) Transactional. The simulation does a tracking of the transport chain as it is
produced in the real world.
Goods are moved from one place to another when some events are produced
(permissions, approvals, load/unload orders, transport orders, etc.) which are
introduced in a transactional manner by the user, or a set of them, in a
centralized or distributed way.
It is the way the closest to the transport chain management, or a part of them,
because of a list of involved actors and organisms (airports, ports, shippers,
customs, etc.). A step-by-step tracking of the goods flow through the model is
obtained.
Its usage, besides management, is the educational value because the step-bystep operation of the transport chain can be shown down to the wished detail
level.
A specific case of these types of models is the simulation of the necessary
document flow to make the goods progress through the transport chain. All the
goods are real ones or fictitious and all the transit requirements are limited to
the ones related to the necessary documents. This is particularly useful in case
of analyzing the impact of new document systems (for example EDI) in terms of
quantity, times, costs face to existing and more conventional information
systems.
2) Stochastic Analysis. The introduction of the different alternatives of
connection from a node to another, also the estimation of normalize distribution
functions (means and standard deviations) in the time and cost parameters of
the nodes and connections, allow us to evaluate the outputs of the model not
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just in average but also as functions of distribution along the time. The choice of
a level of reliance (1 sigma  68%, 2 sigmas  95%, etc.) allow us to set the
average in a min-max strip that indicates the reliance and precision of those
results.
Figure 3.1.
Stochastic analysis example
The use of simulation techniques as "Montecarlo" for the random choice of
paths, times and costs permits to reach a fine grain level that can be even more
precise just adding more random simulations.
These types of models are also know as risk analysis.
3) Optimization. The model does a dynamic optimization of the system in each
clock cycle depending on the chosen criteria. The result is the best strategy to
minimize costs and times or to improve the storage.
The different results according to optimization criteria are very helpful for
resource and service planning, the removal of a bottleneck or to start
investments to improve settlements or transport means.
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Figure 3.2.
Optimal analysis example
4) Scenarios. It consists on comparing the system's behavior face to a same input
depending on different scenarios obtained from a parameters variation on a
base scenario. The comparison is done on any simulation model element along
the time.

Generic system outputs

Nodes.

Connections.
The effects analysis of such or such other politic, what happens if some
changes are applied in the current system, what is the impact of a particular
strategy, these are some of the questions answered by this type of models.
Catastrophes are a particular case. In such models, the impact of the
alternatives over a specific transport chain can be measured with some traffic
expectations. The study of alternative scenarios over a basic catastrophe-like
one permits to study and analyze the potential right actions, to measure its
efficiency, and to improve the creation of decisions and strategies face to those
situations.
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WHAT IF ANALYSIS
INPUT
OUTPUT
E
L
A
P
S
E
D
T I
M
E
U
N I
T
S
EDI
TIME
TIME
Figure 3.3.
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ACTUAL
What if analysis example
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4. SCALABILITY.
As seen, using a reduced set of conceptual elements:
Objects.
Relationships.
Rules.
Events.
It is possible to represent any virtual transport chain using a model (as complex as needed) and
the recursive usage and the adequate organization of the previous elements.
New particularities that can appear in the transport chains can also be conveniently represented
with the current design conceptual elements. Even if the situation is worst due to unexpected
elements and real processes, the impact on the current system would be reduced to an
enlargement of attributes in nodes and connections. This is a situation that this system can
handle.
On the other side, the design elements are valid for any type of transport wanted to be
represented (ground, air, sea, mixed, etc.) even if it is fictitious or belonging to a different group
other than transport (document management, manufacture processes, generic dynamic systems,
etc.).
The systems representation can also be handled with a global or very detailed view. Several
systems can also be grouped in just one and concurrently analyze its dynamic behavior. The
interest of such simulations is not exclusive of big national or international entities but also of
organism and individual users. Politics, strategies and daily management of all these organisms
can be improved using this tool and realistic simulations that allow better decisions in all the
domains of competence.
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Finally, the system is thought to work in distributed environments in such a manner that the
different actors can interact concurrently and simultaneously visualize the same results, and this
do not avoid its local use and mono-task usage for individual users.
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5. VTC API.
The VTC Application Program Interface is the instrument of the user for interaction with the model.
These are the basic functions:
 The models function permits the interactive management of the models and
scenarios: creation, storage, load and update.
 The orders function is the in charge of managing command files VTC: creation,
storage, load and update.
 The function to execute permits to establish run parameters, types of results to
obtain and the monitoring (graph and numerically) step by step, of the model
(information from the nodes and transported goods flows).
 The function outputs permits to analyze with detail each and every one of the
aspects of the results obtained in each step and to export them to conventional files
to be treated additionally by other analysis instruments (Worksheets, statistic
packages, etc.)
 It will exist generic functions such as print or help that are applied to the context to
each one of the different functions.
It will be understood that the API will be conditioned to the type of machine and operative system
in the one that is implemented, and mainly the graphic interface. In any case the handled concepts
will be independent of such restrictions.
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6. ANALYSIS OF DEVELOPMENT TOOLS.
An analysis of the different commercial tools oriented to the representation and analysis of
dynamic systems has been made in order to check if some of them are capable of simulate the
transport virtual chains as they have been conceptually designed.
The parameters have been measured in a scale from 0 to 5. When the information is not known a
question mark has been used (?). These are the used parameters with the description of the most
important contents:
1) Problem suitability. The tool capacity to represent the transport virtual chain
using the design conceptual elements (nodes, connections, rules and events)
and its adjustment to functional and user requirements (numerical and graphical
outputs, user concurrent interaction, scalability, etc.).
2) Development environment. The following aspect of tool operability have been
measured:

Platforms. Hardware/software requirements and computer systems
where it can be executed, memory and storage needs). Local network.
Multi-user.

Development. If it is an integrated environment (development,
execution, analysis, debugging). Graphical edition (graphical
development environment, drag and drop, design elements template
libraries). Native development language (powerful, easiness). Real
problems times of development. Tool learning. On-line help.
3) Connectivity. The tool interface is measured along with other programmatic
languages to complement the model logic (C++ and other languages) and
external databases (ODBC, SQL, etc.).
4) Reporting. The output information produced by the tool is measured in terms of
quantity and quantity of the information, degree of detail, different type of
graphics, graphical animation of the dynamic process, virtual reality graphics,
etc. The results post-process capacity is also measured (data-sheet interaction,
ASCII files, etc.).
5) Portability. The tool's possibilities to generate models that can be executed
outside the development environment is also measured (executables, dynamic
libraries, run-time).
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6) Technical support. The technical support of the providers face to tool
problems or learning the tool has also been measured.
7) Experience in the group. The development group's knowledge of the tool is
being measured.
8) Prizes. The tool and the development license prizes have been measured.
All well-know dynamic-system-simulation-oriented commercial tools have been evaluated. The
measured tools are the following:

Dynamo Plus Pugh Roberts Associates Consulting, Inc. Five Lee Street,
Cambridge MA 02139, (617) 864-8800.
Dynamic-system-oriented tool according to the Forrester methodology. The
models are built as a set of equations that reflect the cause relations among
variables. Its most frequent use is for complex econometric models.
MS-DOS and Windows platforms. Requirements 286 or superior, 4 Mb RAM,
VGA and about 5Mb HD.

Vensim. Window System Inc.
Dynamic-system-oriented tool according to Forrester's methodology or even
free methodology. Its most frequent use is for complex econometric models.
Windows and Macintosh platforms.

Arena. System Modeling Corporation. 504 Beaver Street, Sewickley, Pa 15143,
(412) 741-3727.
General-dynamic-system-oriented tool. It is used in plenty of areas
(manufacture, transport, electronic circuits, communications, etc.) where there
exists customized templates to ease the model design.
Windows 95 and Windows NT platforms.

ILOG Views. ILOG SA. C/ Gobelas 13, 28023 Madrid, Spain (Tel. +34 1
3729551).
General Range. Data Visualization: Command and Control, Geographic
Information Systems, Traffic Monitoring, Vehicle Tracking Systems.
Resource Optimization: Airport Counter, Gate and Belt Allocation, Fleet
Management and Equipment Scheduling, Distribution planning, Crew Allocation,
Traffic planning, Timetabling, Warehouse management.
Windows 95, Windows NT and UNIX platforms.
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
Witness. Addlink Software Científico. C/ Rosellón 205, Barcelona (Tel. +34 3
4154904).
General Applications. Logistic Analysis, Impacts in goods distribution,
Analysis of costs on products, Chemical mixes, Time processing, Identification
of bottle necks in processing, Storage, Process quality.
Windows 95 and Windows NT platforms.
CRITERIA
DINAMO+
VENSIM
ARENA
ILOG
WITNESS
1. Problem suitability
2
3
4
4
1
2. Develop. environm.
1
4
5
4
2
3. Connectivity
2
3
5
5
?
4. Reporting
0
2
4
4
1
5. Portability
0
3
5
4
2
6. Technical support
?
3
4
3
3
7. Experience (group)
0
0
4
1
0
8. Prizes
3
4
4
5
4
8
22
35
30
13
TOTAL
The best grades are for Arena. Therefore as a demand to the involved parts in the project, this is
the tool chosen as basic element to develop Virtual Transport Chains.
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