Shahrood University of Technology Journal of AI and Data Mining 2322-5211 2 2 2014 07 01 Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes 105 112 292 10.22044/jadm.2014.292 EN N. Nekooghadirli Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, R. Tavakkoli-Moghaddam School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran V.R. Ghezavati Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran Journal Article 2013 07 08 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. https://jad.shahroodut.ac.ir/article_292_819368a0b1a03d88b4d12e3805b79d9a.pdf