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Beetle antennae search (BAS) is an efficient meta-heuristic algorithminspired by foraging behaviors of beetles. This algorithm includes severalparameters for tuning and the existing results are limited to solve singleobjective optimization. This work pushes forward the research on BAS byproviding one variant that releases the tuning parameters and is able to handlemulti-objective optimization. This new approach applies normalization tosimplify the original algorithm and uses a penalty function to exploitinfeasible solutions with low constraint violation to solve the constraintoptimization problem. Extensive experimental studies are carried out and theresults reveal efficacy of the proposed approach to constraint handling.

Beetle Antennae Search without Parameter Tuning (BAS-WPT) for Multi-objective Optimization