Introduction to Evolutionary Multiobjective Optimization
Multiobjective Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Modeling the global freight transportation system: a multi-level modeling perspective
Proceedings of the Winter Simulation Conference
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Simulation and optimization have been successfully combined to solve real-world decision making problems. However, there is no formal structure to define the integration between simulation and optimization. This deters the development of simulation-based optimization methods that have a proper balance between the desired features (i.e. generality, efficiency, high-dimensionality and transparency). This research provides two contributions to the problem above by providing: 1) the design of the framework that facilitates the fulfillment of the aforementioned features; 2) the implementation of the framework in Java. The proposed framework is developed based on Zeigler's modeling and simulation framework and the phases of an optimization study in operations research. The test and evaluation show that the desired features are successfully satisfied.