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Results tagged with multi-objective-optimization
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Multi-objective optimization is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Involve two or more optimization goals that are conflicting, meaning that improvement to one objective comes at the expense of another objective. The two methods for perform a multi-objetive-optimization are Pareto and scalarization.
2
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Need a multi-optimization environment or plugin in Anylogic
Well, if you can do multi-objective optimization in Anylogic, you could assign weights to all of your cost functions and consolidate them into a unique objective function. In that way, you obtain one …
2
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Which Python package is suitable for multiobjective optimization
Just adding two more options. Pymoo is a good option, it has several algorithms and functionality for creating your own. And Pysamoo is the version for surrogated (multiobjective) optimization.
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Multi objective optimization is giving wrong results
Pymoo always minimize so, as you did, it is needed to convert max priority to min -priority. If your results are expressed in terms of priority instead of -priority, and sorted in base of the first co …
8
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Determining the optimize lambda in Multi-Objective Optimization
Another approach could be generating the Pareto Frontier, solving the problem several times for different values of lambda, using a Weighted sum algorithm (see this or this).