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A Non-dominated Sorting Ant Colony Optimization Algorithm Approach to the Bi-objective Multi-vehicle Allocation of Customers to Distribution Centers | ||
Journal of Optimization in Industrial Engineering | ||
مقاله 6، دوره 9، شماره 19، خرداد 2016، صفحه 61-74 اصل مقاله (2.19 M) | ||
نوع مقاله: Original Manuscript | ||
شناسه دیجیتال (DOI): 10.22094/joie.2016.230 | ||
نویسندگان | ||
Jafar Bagherinejad* ؛ Mina Dehghani | ||
University of Alzahra | ||
چکیده | ||
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. | ||
کلیدواژهها | ||
Bi-objective optimization؛ capacitated allocation؛ distribution centers؛ non-dominated sorting ant colony optimization؛ NSGA-II | ||
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