Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
A cooperative parallel meta-heuristic for the vehicle routing problem with time windows
Computers and Operations Research
Explicit and Emergent Cooperation Schemes for Search Algorithms
Learning and Intelligent Optimization
JABAT middleware as a tool for solving optimization problems
Transactions on computational collective intelligence II
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Cooperation as a problem-solving strategy is a widely used approach to solving complex hard optimization problems. It involves a set of highly autonomous programs (agents), each implementing a particular solution method, and a cooperation scheme combining these autonomous programs into a single problem-solving strategy. It is expected that such a collective of agents can produce better solutions than any individual members of such collective. The main goal of the paper is to propose a new population-based cooperative search approach for solving the Vehicle Routing Problem. It uses a set of search procedures, which attempt to improve solutions stored in a common, central memory. Access to a single common memory allows exploitation by one procedure solutions obtained by another procedure in order to guide the search through a new promising region of the search space, thus increasing chances for reaching the global optimum.