The multiple server location problem

“…This assumption is known as the "mill pricing"; petrol stations and paid car parking areas are examples of mill pricing application. 4 The closest research paper to this work is Aboouee Mehrizi et al [1]. However, the contributions of this research to the research literature are as follows:…”

Section: Introductionmentioning

confidence: 98%

“…Berman and Drezner [4] formulated a facility location problem within a M/M/m (multi-server) queuing framework. Syam [43] presented a nonlinear multi-server location-allocation problem to minimize total costs of the system.…”

Section: Introductionmentioning

confidence: 99%

Bi-objective vibration damping optimization for congested location–pricing problem

Hajipour

Farahani

2016

Computers & Operations Research

View full text Add to dashboard Cite

This paper presents a bi-objective mathematical programming model for the restricted facility location problem, under a congestion and pricing policy. Motivated by various applications such as locating server on internet mirror sites and communication networks, this research investigates congested systems with immobile servers and stochastic demand as M/M/m/k queues. For this problem, we consider two simultaneous perspectives; (1) customers who desire to limit waiting time for service and (2) service providers who intend to increase profits. We formulate a bi-objective facility location problem with two objective functions: (i) maximizing total profit of the whole system and (ii) minimizing the sum of waiting time in queues; the model type is mixed-integer nonlinear. Then, a multi-objective optimization algorithm based on vibration theory (so-called multi-objective vibration damping optimization (MOVDO)), is developed to solve the model. Moreover, the Taguchi method is also implemented, using a response metric to tune the parameters.The results are analyzed and compared with a non-dominated sorting genetic algorithm (NSGA-II) as a well-developed multi-objective evolutionary optimization algorithm. Computational results demonstrate the efficiency of the proposed MOVDO to solve large-scale problems.

show abstract

“…In a recent paper, Berman and Drezner (2007) introduced a model in which they generalized the type of facilities considered by Wang et al (2002) by modeling the facilities as * Corresponding author M/M/k (k ≥ 1) queuing systems. Given p homogenous servers, the problem is to find locations for the service facilities and to allocate the p servers among them.…”

Section: Introductionmentioning

confidence: 99%

“…Given p facilities, the objective function in Wang et al (2002) and in Berman and Drezner (2007) is to minimize the sum of the travel cost and waiting time cost for all customers. In this paper, while the number of servers is also a decision variable, we consider a more realistic objective function which, in addition to travel and waiting time costs, also includes the fixed cost of opening facilities and the variable cost of the servers.…”

Section: Introductionmentioning

confidence: 99%

Location and allocation of service units on a congested network

2008

View full text Add to dashboard Cite

We consider the problem of locating facilities and allocating servers on a congested network (LASCN). Demands for service that originate from the nodes are assumed to be Poisson distributed and the servers provide a service time that is exponentially distributed. The objective is to minimize the total cost of the system which includes a fixed installation cost, a variable server cost, a cost associated with travel time and a cost associated with the waiting time in the facility for all the customers. The problem is formulated using non-linear programming and subsequently analyzed. Results for exact and approximate solution approaches are reported. We also show that we can modify the approaches to solve the LASCN with constraints limiting both the travel time to the servers and the waiting time of customers.

show abstract

The multiple server location problem

Cited by 87 publications

References 21 publications

Tabu Search and Hybrid Genetic Algorithms for Quadratic Assignment Problems

Tabu Search and Hybrid Genetic Algorithms for Quadratic Assignment Problems

Bi-objective vibration damping optimization for congested location–pricing problem

Location and allocation of service units on a congested network

Contact Info

Product

Resources

About