An overview of representative problems in location research
Management Science
A tabu search procedure for multicommodity location/allocation with balancing requirements
Annals of Operations Research - Special issue on Tabu search
Parallel simulated annealing algorithms
Journal of Parallel and Distributed Computing
Cluster analysis and mathematical programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Computers and Operations Research
Global optimization properties of parallel cooperative search algorithms: a simulation study
Parallel Computing - High performance computing in operations research
Tabu Search
Essays and Surveys in Metaheuristics
Essays and Surveys in Metaheuristics
Variable Neighborhood Decomposition Search
Journal of Heuristics
Toward Self-Integrating Software Applications for Supply Chain Management
Information Systems Frontiers
Cooperative Parallel Tabu Search for Capacitated Network Design
Journal of Heuristics
Heuristic Methods for Large Centroid Clustering Problems
Journal of Heuristics
Heuristic concentration for the p-median: an example demonstrating how and why it works
Computers and Operations Research
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Cooperative Mult-thread Parallel Tabu Search with an Application to Circuit Partitioning
IRREGULAR '98 Proceedings of the 5th International Symposium on Solving Irregularly Structured Problems in Parallel
A cooperative parallel meta-heuristic for the vehicle routing problem with time windows
Computers and Operations Research
Computational study of large-scale p-Median problems
Mathematical Programming: Series A and B
Heuristic solution of the multisource Weber problem as a p-median problem
Operations Research Letters
A family of facets for the uncapacitated p-median polytope
Operations Research Letters
Metaheuristic Agent Teams for Job Shop Scheduling Problems
HoloMAS '07 Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing
A memetic genetic algorithm for the vertex p-center problem
Evolutionary Computation
Soft computing and cooperative strategies for optimization
Applied Soft Computing
Using machine learning in a cooperative hybrid parallel strategy of metaheuristics
Information Sciences: an International Journal
Flexible job-shop scheduling with parallel variable neighborhood search algorithm
Expert Systems with Applications: An International Journal
A software modeling approach for the design and analysis of cooperative optimization systems
Software—Practice & Experience
A memetic cooperative optimization schema and its application to the tool switching problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
A multi-objective genetic algorithm with path relinking for the p-median problem
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Experiments in parallel constraint-based local search
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Using memory and fuzzy rules in a co-operative multi-thread strategy for optimization
Information Sciences: an International Journal
Targeting the Cell Broadband Engine for constraint-based local search
Concurrency and Computation: Practice & Experience
Information Sciences: an International Journal
GPU-based parallel vertex substitution algorithm for the p-median problem
Computers and Industrial Engineering
Three improved hybrid metaheuristic algorithms for engineering design optimization
Applied Soft Computing
Journal of Global Optimization
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We propose a cooperative multi-search method for the Variable Neighborhood Search (VNS) meta-heuristic based on the central-memory mechanism that has been successfully applied to a number of difficult combinatorial problems. In this approach, several independent VNS meta-heuristics cooperate by asynchronously exchanging information about the best solutions identified so far, thus conserving the simplicity of the original, sequential VNS ideas. The p-median problem (PM) serves as test case. Extensive experimentations have been conducted on the classical TSPLIB benchmark problem instances with up to 11948 customers and 1000 medians, without any particular calibration of the parallel method. The results indicate that, compared to sequential VNS, the cooperative strategy yields significant gains in terms of computation time without a loss in solution quality.