A novel multi-objective optimization algorithm based on artificial algae for multi-objective engineering design problems

There are many diverse fields and applications such as data mining, engineering, operations research, economics, and science can be formulated as multi-objective optimization problems. In this paper, we describe and propose a novel and a useful multi-objective artificial algae algorithm (MO-AAA) to solve multi-objective engineering design problems. Our proposed algorithm, (MO-AAA), is based on the search technique of artificial algae algorithm(AAA) algorithm. MO-ADA applies the elitist non-dominated sorting and crowding distance approach to preserve the diversity among the optimal set of solutions and obtains various non-domination levels, respectively. Also, we evaluate the effectiveness of the proposed algorithm by applying it on different multi-objective benchmark problems (20 challenging benchmark problems from CEC 2009 for unconstrained and constrained multi-objective optimization problems) and engineering design benchmark problems with distinctive features. Finally, our results show that MO-AAA efficiently generates the Pareto front and is easy to implement, promising and competitive compared to other state-of-the-art algorithms considered in this work.

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