the application of multi-objective charged systemsearch algorithm for optimization problems

The charged system search algorithm is a relatively new optimization algorithm developed based on some principles from physics and mechanics. this paper presents an approach in which pareto dominance is incorporated into the charged system search in order to allow this algorithm to handle problems with some multi-objective functions; the proposed algorithm will be called multi-objective charged system search (mocss). well-known mathematical and engineering benchmarks were used to evaluate the proposed algorithm, and the results were compared with those of other new approaches. the results of implementing an algorithm on some test problems show that the proposed algorithm outperforms other algorithms in terms of generational distance, maximum spread, spacing, coverage of two sets, and hypervolume indicator. results of wellknown mathematical examples indicate that an approach is highly competitive and can be considered as a viable alternative to solving multi-objective optimization problems. these results encourage the application of the proposed method to more complex and realworld multi-objective optimization problems. the proposed method can deal with highly nonlinear problems with complex constraints and diverse pareto optimal sets.