Abstract:
This paper addresses a situation in which a firm is willing to locate several new multi-server facilities in a geographical area to provide a service to customers within a queue system. As a new assumption, it is also considered that there is already operating competitors in such system. This paper is going to find the location of facilities in a way that the market share of the entering firm is maximized. To this end, the simultaneous minimization of total cost and the maximum idle time in each facility are considered as two objective functions in the model. The total cost consists of two parts: (1) the fixed cost for opening a new facility, and (2) the operational costs for the customers, which depends on travel time to the facility and the waiting time at the facility. In addition, in order to make the problem more adapted to real-world situations, two new constraints on budget and the number of the servers in each facility are added to the model. Eventually, to tackle the suggested problem, a non-dominated sorting genetic algorithm (NSGA-II) and a non-dominated ranked genetic algorithm (NRGA) are utilized. Finally, the performance of algorithms is investigated by analyzing a set of test problems.
Machine summary:
com A Multi-objective Competitive Location Problem within Queuing Framework Ali Salmasnia a, Mohammad Mousavi-Saleh a and Hadi Mokhtari b, * a Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran b Department of Industrial Engineering, University of Kashan, Kashan, Iran Abstract This paper addresses a situation in which a firm is willing to locate several new multi-server facilities in a geographicalarea to provide a service to customers within a queue system.
Competitive location problem; �/�/�/� queuing system; Multi-server facilities; Multi-objective modeling; NSGA-II, NRGA Keywords: 1.
Benati and Hansen (2002) studied an optimization model for finding the location of new facilities in competitive markets with random utility function.
Beresnev (2013) proposed a mathematical model generalizing the well-known facility location problem in order to maximize the market share, and used a branch and bound algorithm to solve the model.
In this model, the objective function aims to maximize market share for entering firm and minimize the total cost including fixed cost for opening a new facility, traveling cost, waiting cost, and the maximum idle time in each facility.
In this model, the first objective function aims to maximize the market share for entering firm by minimizing the total cost which includes the fixed cost for opening a new facility, traveling cost, and waiting cost.
Biesinger B, Hu B, Raidl G, (2016), Models and algorithms for competitive facility location problems with different customer behavior.