A Non-dominated Sorting Ant Colony Optimization Algorithm Approach to the Bi-objective Multi-vehicle Allocation of Customers to Distribution Centers

Abstract

Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimization tool for solving this problem. The proposed methodology is based on a new variant of ant colony optimization (ACO) specialized in multi-objective optimization problem. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this purpose. For ensuring the robustness of the proposed method and giving a practical sense of this study, the computational results are compared with those obtained by NSGA-II algorithm. Results show that both NSACO and NSGA-II algorithms can yield an acceptable number of non-dominated solutions. In addition, the results show while the distribution of solutions in the trade-off surface of both NSACO and NSGA-II algorithms do not differ significantly, the computational CPU time of NSACO is considerably lower than that of NSGA-II. Moreover, it can be seen that the fast NSACO algorithm is more efficient than NSGA-II in the viewpoint of the optimality and convergence.

Keywords

• Bi-objective optimization
• capacitated allocation
• distribution centers
• non-dominated sorting ant colony optimization
• NSGA-II