Practical Handbook of Genetic Algorithms: New Frontiers
Practical Handbook of Genetic Algorithms: New Frontiers
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Reactive GRASP: An Application to a Matrix Decomposition Problem in TDMA Traffic Assignment
INFORMS Journal on Computing
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
A variable neighbourhood search algorithm for job shop scheduling problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
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In the process of searching for better solutions, a metaheuristic can be guided to regions of promising solutions using the acquisition of information on the problem under study. In this work this is done through the use of reinforcement learning. The performance of a metaheuristic can also be improved using multiple search trajectories, which act competitively and/or cooperatively. This can be accomplished using parallel processing. Thus, in this paper we propose a hybrid parallel implementation for the GRASP metaheuristics and the genetic algorithm, using reinforcement learning, applied to the symmetric traveling salesman problem.