We incorporate a new adaptive-based mutation operator (MODE) to create more diversity and enhance convergence rate among candidate solutions which provide better solutions to help the evolution. In this method, we use the Pareto optimality principle. Firstly, the new homeostasis factor-based mutation operator incorporates multi-objective differential evolution algorithms (MODE). In the validation process, the proposed method is validated in two steps. In this paper, we propose a novel multi-objective DE algorithm to deal with this problem. Most of the existing algorithms face the problem of diversity loss and convergence rate. This paper tries to extend the idea of single-objective differential evolution (DE) algorithm to a multi-objective algorithm.
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