Approximation of solutions for location problems
Journal of Optimization Theory and Applications
NP-Hard, capacitated, balanced p-median problems on a chain graph with a continuum of link demands
Mathematics of Operations Research
Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Discrete Applied Mathematics - Special volume: viewpoints on optimization
Fast, efficient and accurate solutions to the Hamiltonian path problem using neural approaches
Computers and Operations Research
Algorithmic approaches for solving the euclidean distance location and location-allocation problems
Algorithmic approaches for solving the euclidean distance location and location-allocation problems
Region-rejection based heuristics for the capacitated multi-source Weber problem
Computers and Operations Research
Accelerating convergence in the Fermat-Weber location problem
Operations Research Letters
Heuristics for the single source capacitated multi-facility Weber problem
Computers and Industrial Engineering
Beam search heuristics for the single and multi-commodity capacitated Multi-facility Weber Problems
Computers and Operations Research
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The capacitated multi-facility Weber problem is concerned with locating I capacitated facilities in the plane to satisfy the demand of J customers with the minimum total transportation cost of a single commodity. This is a nonconvex optimization problem and difficult to solve. In this work, we focus on a multi-commodity extension and consider the situation where K distinct commodities are shipped subject to capacity constraints between each customer and facility pair. Customer locations, demands and capacities for each commodity, and bundle restrictions are known a priori. The transportation costs, which are proportional to the distance between customers and facilities, depend on the commodity type. We address several location-allocation and discrete approximation heuristics using different strategies. Based on the obtained computational results we can say that the alternate solution of location and allocation problems is a very efficient strategy; but the discrete approximation has excellent accuracy.