Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The location-routing problem: considerations in physical distribution system design
Computers and Operations Research
Models for multimode multicommodity location problems with interdepot balancing requirements
Annals of Operations Research
A parallel branch-and-bound algorithm for multicommodity location with balancing requirements
Computers and Operations Research
Capacitated facility location: separation algorithms and computational experience
Mathematical Programming: Series A and B - Special issue on computational integer programming
Computers and Operations Research
A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands
Computers and Operations Research
Tabu Search
Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
Heuristic solutions to multi-depot location-routing problems
Computers and Operations Research
A Bundle Type Dual-Ascent Approach to Linear Multicommodity Min-Cost Flow Problems
INFORMS Journal on Computing
A column generation approach to capacitated p-median problems
Computers and Operations Research
A scatter search-based heuristic to locate capacitated transshipment points
Computers and Operations Research
Efficient Production-Distribution System Design
Management Science
Solution method for the location planning problem of logistics park with variable capacity
Computers and Operations Research
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In this paper, we introduce a capacitated plant location problem with multicommodity flow. Given a set of potential plant sites and a set of capacitated arcs linking plants, transshipment points and customers, the aim is to determine where to locate plants and how to move flows from open plants to customers through a set of transshipment points. This model extends the classical capacitated plant location problem by introducing a multicommodity flow problem in the distribution issue. The combination of the location problem and the flow distribution problem is reasonable and realistic since both of them belong to strategic planning horizons. We propose a Lagrangean-based method, including a Lagrangean relaxation, a Lagrangean heuristic and a subgradient optimization, to provide lower and upper bounds of the model. Then, we employ a Tabu search to further improve upper bounds provided by the Lagrangean procedure. The computational results demonstrate that our solution method is effective since gaps between the upper and lower bound are on average around 2%.