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Nekooghadirli, N., Tavakkoli-Moghaddam, R., Ghezavati, V.R.. (1393). Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes. , 2(2), 105-112. doi: 10.22044/jadm.2014.292
N. Nekooghadirli; R. Tavakkoli-Moghaddam; V.R. Ghezavati. "Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes". , 2, 2, 1393, 105-112. doi: 10.22044/jadm.2014.292
Nekooghadirli, N., Tavakkoli-Moghaddam, R., Ghezavati, V.R.. (1393). 'Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes', , 2(2), pp. 105-112. doi: 10.22044/jadm.2014.292
Nekooghadirli, N., Tavakkoli-Moghaddam, R., Ghezavati, V.R.. Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes. , 1393; 2(2): 105-112. doi: 10.22044/jadm.2014.292

Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes

Journal of AI and Data Mining
مقاله 2، دوره 2، شماره 2، مهر 2014، صفحه 105-112    اصل مقاله (1.06 M)
نوع مقاله: Original/Review Paper
شناسه دیجیتال (DOI): 10.22044/jadm.2014.292
نویسندگان
N. Nekooghadirli* 1؛ R. Tavakkoli-Moghaddam2؛ V.R. Ghezavati3
1Department of Industrial Engineering, South Tehran Branch, Islamic Azad University,
2School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran
3Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
چکیده
An integrated model considers all parameters and elements of different deficiencies in one problem. This paper presents a new integrated model of a supply chain that simultaneously considers facility location, vehicle routing and inventory control problems as well as their interactions in one problem, called location-routing-inventory (LRI) problem. This model also considers stochastic demands representing the customers’ requirement. The customers’ uncertain demand follows a normal distribution, in which each distribution center (DC) holds a certain amount of safety stock. In each DC, shortage is not permitted. Furthermore, the routes are not absolutely available all the time. Decisions are made in a multi-period planning horizon. The considered bi-objectives are to minimize the total cost and maximize the probability of delivery to customers. Stochastic availability of routes makes it similar to real-world problems. The presented model is solved by a multi-objective imperialist competitive algorithm (MOICA). Then, well-known multi-objective evolutionary algorithm, namely anon-dominated sorting genetic algorithm II (NSGA-II), is used to evaluate the performance of the proposed MOICA. Finally, the conclusion is presented.
کلیدواژه‌ها
Multi-objective imperialist competitive algorithm؛ Location-routing-inventory problem؛ Probabilistic routes؛ Multi periods
آمار
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