Designing a Framework for Solving Multiobjective Simulation Optimization Problems
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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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