Human-Centered Engineering
Operations Research Optimization
Aptima’s Operations Research Optimization (ORO) solutions
identify the right mix of people, systems, and tools to best meet
mission requirements and budget constraints. Our algorithms
match the available resources needed for completing a
mission—individuals with different abilities, levels of expertise,
and qualifications, systems and automation, and equipment—
with the set of tasks that must be accomplished. The result is
that our customers have the right mix of people, systems, and
tools to specifically match what is required for mission success.
Reduce Extraneous Resources
Our approach examines the mission task, determines what
resource or resources are required—human, system, or a
combination thereof—and matches the two in the best way
possible. It considers not only the sheer number of available
resources that can perform the task, but how often the task
occurs. This approach reduces extraneous resources—and
costs—within the organization by eliminating resources that
have only one specific task.
Allocate the Right Resources
ORO’s five step process begins by working with the customer
organization to identify all available resources (Collection).
Next, the tasks required by the mission are defined
(Processing). As the resources and tasks are paired together,
each pairing is analyzed (Evaluation)and then optimized to
maximize the probability of success, minimize the time to
completion, and minimize costs (Optimization). Finally, with
the optimal mix of resources and tasks identified, resources
can be allocated (Assignment).
Balance Tasking
Aptima’s innovative top-down/bottom-up approach balances
the needs of the mission within a particular organization with
the available resources—the actual knowledge and skills of the
individuals, and system and tool capabilities. This means no one
resource will be heavily overloaded while another is underloaded.
Explore Tradeoffs, Future Resources
Aptima’s algorithms not only identify the right resources for
the mission, but also help examine tradeoffs and incorporate
future resources. For example, the task may be done with
three individuals and one system, but this solution exceeds
the budget. Alternatively, the algorithm identifies another
option, such as providing additional training for two individuals
to meet the tasking needs within budget.
For more information contact Danielle Ward, [email protected], 781-496-2479
© 2015 Aptima, Inc.