482 research outputs found
Designing a Framework for Solving Multiobjective Simulation Optimization Problems
Multiobjective simulation optimization (MOSO) problems are optimization
problems with multiple conflicting objectives, where evaluation of at least one
of the objectives depends on a black-box numerical code or real-world
experiment, which we refer to as a simulation. This paper describes the design
goals driving the development of the parallel MOSO library ParMOO. We derive
these goals from the research trends and real-world requirements that arise
when designing and deploying solvers for generic MOSO problems. Our specific
design goals were to provide a customizable MOSO framework that allows for
exploitation of simulation-based problem structures, ease of deployment in
scientific workflows, maintainability, and flexibility in our support for many
problem types. We explain how we have achieved these goals in the ParMOO
library and provide two examples demonstrating how customized ParMOO solvers
can be quickly built and deployed in real-world MOSO problems
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