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Performance Evaluation of NSGA-III and SPEA2 in Solving a Multi-Objective Single-Period Multi-Item Inventory Problem

Different evolutionary algorithms perform differently while solving the same optimization problem. Therefore, performance evaluation becomes a field of interest while selecting an appropriate algorithm for a given situation. In this paper, Non-Dominated Sorting Genetic Algorithm-III (NSGA-III) and Strength Pareto Evolutionary Algorithm (SPEA2) were evaluated based on a comparative analysis. The comparison was established upon their performances for solving a simulated multi-objective single-period multi-item inventory problem. The results display that the SPEA-II outperformed NSGA-III with spacing, generational distance and hypervolume as performance evaluation metrics.