Stochastic Methods of Operations Research

Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
PART III
PART III.
INVENTORY THEORY
is a research field within operations research that finds optimal
design of inventory systems both from spatial as well as temporal
point of view to minimize costs. It studies the decisions faced by
firms and the military in connection with manufacturing,
warehousing, spare part allocation etc. It provides mathematical
basis for logistics.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Basic deterministic problems. EOQ.
LECTURE 9
Basic deterministic models.
- warehouse: the ware is consumed continuously (driving fuel,
draught beer,...)
- costs: delivery, storage, deficit
- task: when and how much to restock in order to minimize costs
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model without deficit
Deterministic model without deficit
Assumptions of the simplest model:
• the good/ware is infinitely divisible
• consumption of λ units per unit of time (known, given,
uniform)
• warehouse capacity unconstrained, height of order
unconstrained, goods don’t get old
• costs of one delivery are independent of the amount
• no deficit allowed
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model without deficit
Notation:
• cs - storage costs for 1 unit of good and 1 unit of time
• cd - costs (price) for 1 order (delivery), regardless of its size Q
• S(t) - size of inventory at time t ∈ [0, T ], i.e. S(t) = Q − λt
for t ∈ [0, T ] = [0, Q/λ]
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model without deficit
Storage costs:
• for good left from the warehouse in the interval [t, t + ∆t]:
cs [S(t) − S(t + ∆t)]t + o(∆t)
• overall storage costs between 2 deliveries (generally):
cs
RT
0
S(t)dt − cs S(T )T
• in the simple case with S(t) = Q − λt, T = Q/λ, S(T ) = 0:
λcs T 2 /2
Q52. Derive.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model without deficit
Overall costs:
2
• overall costs for 1 period: cs Q
2λ + cd
λ
• number of deliveries per unit of time: v = Q
• overall costs per unit of time:
2
λ
C (Q) = (cs Q
2λ + cd ) Q = cs Q/2 + cd λ/Q
Q53. Derive.
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spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model without deficit
Optimization:
• we look for Q̂ such that C (Q̂) = minQ C (Q)
• results:
p
Q̂ = 2λcd /cs
T̂ = Q̂/λ,
√
C (Q̂) = 2λcd cs
Q54. Derive.
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 1
LECTURE 10
Deterministic model with deficit (1)
Deficit costs proportional to its volume and duration:
Notation:
• c − - deficit costs for 1 unit of good and 1 unit of time
• T - interval between deliveries (unknown)
• T1 - duration of deficit
• Q - overall demand on interval [0, T ]
• S - unsatisfied demand
• Q − S - satisfied demand
Goal: C (T , T1 ) → min or C (Q, S) → min
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Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 1
Soňa Kilianová
spring semester 2013
Lectures on SMOR
64 / 77
Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 1
Costs as function of Q, S for period T between deliveries:
2
• storage: cs (Q−S)
2λ
S2
• deficit: c − 2λ
• delivery: cd
• overall costs per unit of time:
2
2
S
C (Q, S) = [cs (Q−S)
+ c − 2λ
+ cd ] Qλ
2λ
Q55. Derive.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 1
Optimization:
• we look for Q̃, S̃ such that C (Q̃, S̃) = minQ,S C (Q, S)
• results:
cs
S̃ = Q̃ cs +c
(< Q̃)
−
− 1/2
s
Q̃ = Q̂ c c+c
−
where Q̂ is optimal size in problem without deficit
Q56. Derive.
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 2
Deterministic model with deficit (2)
Deficit costs proportional to its volume only:
Costs as function of Q, S for period T between deliveries:
2
• storage: cs (Q−S)
2λ
• deficit: c − S
• delivery: cd
• overall costs per unit of time:
2
C (Q, S) = [cs (Q−S)
+ c − S + cd ] Qλ
2λ
Q57. Derive.
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spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 2
Optimization:
• we look for Q ? , S ? such that C (Q ? , S ? ) = minQ,S C (Q, S)
• results: p
S? =
if λ ≥ 2cd cs /(c − )2 ,
otherwise
if λ ≥ 2cd cs /(c − )2 ,
otherwise
2λcd /cs
Q? =
6∃
0
6∃
Q58. Derive.
Homework: 37, 38, 42.
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Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Stochastic problem with signaling
LECTURE 11
Stochastic models
Stochastic problem with signaling
Notation:
• λ - random consumption per unit of time
• λ̄ = E(λ)
• r - signaling threshold (at which order is made)
• δ - duration needed for delivery
• ρ - average amount of inventory at the moment of delivery
• Q - size of order (delivery)
Goal: E(C (Q, r )) → min
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spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Deterministic model with deficit, type 1
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Stochastic problem with signaling
Computations:
• average volume of inventory at delivery: ρ = r − δ λ̄
λ̄
• E(C (Q, r )) = cs ( Q2 + r − δ λ̄) + cd Q
+ D(r , Q)
where D(r , Q) is lost due to deficit
Q59. Derive.
Other notation:
• λδ - random consumption on interval of length δ. Deficit
appears when λδ > r .
• fδ - probabilistic density of λδ .
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Types of deficit costs
Two options for deficit:
1. proportional to number of deficits (how many orders per unit
of time ends up in deficit, but independent of its size)
R∞
D(r , Q) = c − P(λδ > r ) Qλ̄ = c − Qλ̄ r fδ (η)dη
2. proportional to average size of deficit
D(r , Q) = c − P(λδ > r ) Qλ̄ E(λδ − r |λδ − r > 0) =
R∞
c − Qλ̄ r (η − r )fδ (η)dη
Q60. Derive.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
72 / 77
Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
Stochastic problem with periodic control
Stochastic problem with periodic control
The size of inventory is controlled in regular time intervals T .
Depending on the current state of inventory we re-stock to level R.
Computations:
• overall expected costs per unit of time:
E(C (R, T )) = cs (R − λ̄δ − λ̄ T2 ) + cd T1 + D(R, T )
Q61. Derive.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
The newsvendor problem
LECTURE 12
The newsvendor problem
- one-shot order
Notation:
• D - random demand with density f
• Q - size of order (delivery)
• if D > Q, q is the lost profit per unit of good
• if Q > D, the unsold goods is sold with loss r
Soňa Kilianová
spring semester 2013
Lectures on SMOR
74 / 77
Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
The newsvendor problem
Computations:
• vendor’s loss:
q(D − Q) of D > Q
r (Q − D) of D < Q
• expected loss:
R
E(C (Q)) = r
Q
−∞ (Q
− D)f (D)dD + q
R∞
Q
(D − Q)f (D)dD
Q62. Derive.
Goal: E(C (Q)) → min
Homework: 48, 50, 52, 56, 57, 58.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
A multi-item model
A multi-item model
Notation:
• λi - demand for goods i per unit of time
• csi - storage cost for unit of good i per unity of time
• cd - cost of order (delivery), independent of its size
• Qi - size of order of i-th good
• T - interval between deliveries
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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Part I: Markov chains
Part II: Queueing theory
Part III: Inventory theory
FMFI UK
A multi-item model
Computations:
• overall costs (for delivery and storage) per unit of time:
C (T ) = cd T1 +
PN
λi T
i=1 csi 2
Optimization:
• we look for T̂ such that C (T̂ ) = minT C (T )
• results:
T̂ =
2c
PN d
i=1 csi λi
1/2
Q63. Derive.
Soňa Kilianová
spring semester 2013
Lectures on SMOR
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