The balance between the objective function and constrained conditions is a common challenge faced by existing constrained multiobjective optimization algorithms.To address this issue,a constrained multiobjective optimization algorithm based on adaptive search strategy(ASSCMO)is proposed.To validate the performance of ASSCMO,it is compared with three excellent constrained multiobjective optimization algorithms through simulation experiments on two sets of benchmark test suites.The experimental results indicate that ASSCMO is more competitive in solving constrained multiobjective problems.
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