Optimization of the flow distribution of e-waste reverse logistics network based on NSGA II and TOPSIS

Abstract

This paper proposes an integrated method based on multi-objective optimization (NSGA II) and multi-attribute decision making (TOPSIS) to analyze the optimal flow distribution of e-waste reverse logistics network. Within the established multi-objective model, objectives concerning economic (total profit), ecological (accumulated energy consumption) performances and loss are considered. For the multi-objective optimization problem, evolutionary algorithm-based NSGA II (improved non-dominated sorting genetic algorithm) is used to obtain Pareto optimal solutions, which constitute the decision-making matrix of multi-attribute decision making, then through the Eigenvector, combined with the subjective preferences of decision makers to determine the weight of each criteria, Finally, TOPSIS is applied to determine the most satisfactory decision point.