NP-Hard, capacitated, balanced p-median problems on a chain graph with a continuum of link demands
Mathematics of Operations Research
Discrete Applied Mathematics - Special volume: viewpoints on optimization
Hybrid evolutionary method for obstacle location-allocation
ICC&IE '94 Proceedings of the 17th international conference on Computers and industrial engineering
Heuristic Methods for Large Centroid Clustering Problems
Journal of Heuristics
Algorithmic approaches for solving the euclidean distance location and location-allocation problems
Algorithmic approaches for solving the euclidean distance location and location-allocation problems
Global optimization of mixed-integer nonlinear programs: A theoretical and computational study
Mathematical Programming: Series A and B
Simulated annealing heuristics for the dynamic facility layout problem
Computers and Operations Research
Genetic subgradient method for solving location-allocation problems
Applied Soft Computing
A simulated annealing heuristic for the capacitated location routing problem
Computers and Industrial Engineering
Planar expropriation problem with non-rigid rectangular facilities
Computers and Operations Research
A guided reactive GRASP for the capacitated multi-source Weber problem
Computers and Operations Research
A hierarchical algorithm for the planar single-facility location routing problem
Computers and Operations Research
Heuristic solution of the multisource Weber problem as a p-median problem
Operations Research Letters
Heuristics for the single source capacitated multi-facility Weber problem
Computers and Industrial Engineering
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Multi-Facility Weber Problem (MFWP), also known as continuous location-allocation problem, entails determining the locations of a predefined number of facilities in a planar space and their related customer allocations. In this paper, we focus on a new variant of the problem known as Single-Source Capacitated MFWP (SSCMFWP). To tackle the problem efficiently and effectively, an iterative two-phase heuristic algorithm is put forward. At the phase I, we aim to determine proper locations for facilities, and during the phase II, assignment of customers to these facilities is pursued. As an alternative solution method, a simulated annealing (SA) algorithm is also proposed for carrying out the phase I. The proposed algorithms are validated on a comprehensive set of test instances taken from the literature. The proposed iterative two-phase algorithm produces superior results when assessed against the proposed SA algorithm as well as a general MINLP Solver known as BARON. The latter is applied to produce optimal solutions for small sized instances and generate upper bound for medium ones.