This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second st...

Three types of fuzzy random programming for capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected value model, chanceconstrained programming and dependent-chance programming. Finally, integrating the network simplex algorithm, fuzzy random simulation and genetic algorithm, a hybrid intelligent algorithm is produced...

We consider a generalization of the discrete Voronoi game, in which consumers with positive purchase power who are located on the vertices of a network wish to connect to the nearest facility. Knowing this, competitive players locate their facilities on vertices, trying to capture the largest possible market share. We study conditions that guarantee the existence of a pure strategy Nash equilib...

The p-facility Hu location problem aims at locating facilities on a competitive environment so as to maximize the market share. While it has been deeply studied in the eld of continuous location, in this paper we study the p-facility Hu location problem on networks formulated as a Mixed Integer Nonlinear Programming problem that can be solved by a branch and bound algorithm. We propose two appr...

Companies pursuing extension of their activities and new companies in establishment phase are using various concepts and techniques to consider location decision, because location greatly a®ects both ̄xed and variable costs and on the overall pro ̄t of the company. This paper suggests a new use of quality function deployment (QFD) for facility location selection problem instead of applying it to ...

In this paper, we present an approximation algorithm achieving approximation guarantee of 2 for the classical uncapacitated facility location problem. The distinguishing feature of our designed algorithm is the overall low running time of ( log ) O m m , where c f m n n = × , c n and f n are the number of cities and facilities. Though the approximation factor is 1.61 in Ref.[1], whereas the run...

Computation of facility location problem for every location in the country is not easy simultaneously. Solving the problem is described by using cluster computing. A technique is to design parallel algorithm by using local search with single swap method in order to solve that problem on clusters. Parallel implementation is done by the use of portable parallel programming, Message Passing Interf...

The traditional, uncapacitated facility location problem (UFLP) seeks to determine a set of warehouses to open such that all retail stores are serviced by a warehouse and the sum of the fixed costs of opening and operating the warehouses and the variable costs of supplying the retail stores from the opened warehouses is minimized. In this paper, we discuss the partial coverage uncapacitated fac...

In this paper we study the facility leasing problem with penalties. We present a primaldual algorithm which is a 3-approximation, based on the algorithm by Nagarajan and Williamson for the facility leasing problem [NW13] and on the algorithm by Charikar et al. for the facility location problem with penalties [CKMN01].

We present e cient algorithms for two problems of facility location. In both problems we want to determine the location of a single facility with respect to n given sites. In the rst we seek a location that maximizes a weighted distance function between the facility and the sites, and in the second we nd a location that minimizes the sum (or sum of the squares) of the distances of k of the site...