Models for multimode multicommodity location problems with interdepot balancing requirements
Annals of Operations Research
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Cooperative Parallel Tabu Search for Capacitated Network Design
Journal of Heuristics
A Simplex-Based Tabu Search Method for Capacitated Network Design
INFORMS Journal on Computing
Polynomial approximation schemes and exact algorithms for optimum curve segmentation problems
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
A first multilevel cooperative algorithm for capacitated multicommodity network design
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search
Operations Research
0-1 reformulations of the multicommodity capacitated network design problem
Discrete Applied Mathematics
Tuning Metaheuristics: A Machine Learning Perspective
Tuning Metaheuristics: A Machine Learning Perspective
A capacity scaling heuristic for the multicommodity capacitated network design problem
Journal of Computational and Applied Mathematics
Matheuristics: Optimization, Simulation and Control
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
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The fixed-cost Capacitated Multicommodity Network Design (CMND) problem is a well known NP-hard problem. This paper presents a matheuristic algorithm combining Simulated Annealing (SA) metaheuristic and Simplex method for CMND problem. In the proposed algorithm, a binary array is considered as solution representation and the SA algorithm manages open and closed arcs. Several strategies for opening and closing arcs are proposed and evaluated. In this matheuristic approach, for a given design vector, CMND becomes a Capacitated Multicommodity minimum Cost Flow (CMCF) problem. The exact evaluation of the CMCF problem is performed using the Simplex method. The parameter tuning for the proposed algorithm is done by means of design of experiments approach. The performance of the proposed algorithm is evaluated by solving different benchmark instances. The results of the proposed algorithm show that it is able to obtain better solutions in comparison with previous methods in the literature.