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A Simple Evolution Strategy to Solve Constrained Optimization Problems |
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Efrén Mezura-Montes proposed some relatively simple, but rather effective mechanisms to enhance the performance of a
multimembered evolution strategy used to solve constrained optimization problems. The approach does not require the use
of a penalty function. Instead, it uses a simple diversity mechanism based on allowing infeasible solutions to remain in the
population. This technique helps the algorithm to find the global optimum despite reaching reasonably fast the feasible region
of the search space. A simple feasibility-based comparison mechanism is used to guide the process towards the feasible region
of the search space. Also, the initial stepsize of the evolution strategy is reduced in order to perform a finer search and a
combined (discrete/intermediate) panmictic recombination technique improves its exploitation capabilities.
The source code of this approach is available here.
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