Hub Covering Location Problem Considering Queuing and Capacity Constraints

Journal of Optimization in Industrial Engineering

مقاله 11، دوره 11، شماره 1 - شماره پیاپی 23، خرداد 2018، صفحه 143-156   

نوع مقاله: Original Manuscript

شناسه دیجیتال (DOI): 10.22094/joie.2017.351.0

نویسندگان

Mehdi Seifbarghy^{* 1}؛ Mojtaba Hemmati²؛ Sepideh Soltan Karimi²

¹Associate Professor, Department of Industrial Engineering, Alzahra University, Tehran, Iran

²MSc, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

چکیده

In this paper, a hub covering location problem is considered. Hubs, which are the most congested part of a network, are modeled as M/M/C queuing system and located in placeswhere the entrance flows are more than a predetermined value.A fuzzy constraint is considered in order to limit the transportation time between all origin-destination pairs in the network.On modeling, a nonlinear mathematical program is presented.Then, the nonlinear constraints are convertedto linear ones.Due to the computational complexity of the problem,genetic algorithm (GA),particle swarm optimization (PSO)based heuristics, and improved hybrid PSO are developedto solve the problem. Since the performance of the given heuristics is affected by the corresponding parameters of each, Taguchi method is appliedin order to tune the parameters. Finally,the efficiency ofthe proposed heuristicsis studied while designing a number of test problems with different sizes.The computational results indicated the greater efficiency of the heuristic GA compared to the other methods for solving the problem

کلیدواژه‌ها

Hub covering location؛ Queuing system؛ Congestion؛ Genetic Algorithm؛ Hybrid particle swarm optimization algorithm