A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Meta-heuristics: The State of the Art
ECAI '00 Proceedings of the Workshop on Local Search for Planning and Scheduling-Revised Papers
Performance of Various Computers Using Standard Linear Equations Software
Performance of Various Computers Using Standard Linear Equations Software
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
A survey of multi-agent organizational paradigms
The Knowledge Engineering Review
Active-guided evolution strategies for large-scale capacitated vehicle routing problems
Computers and Operations Research
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
A comprehensive analysis of hyper-heuristics
Intelligent Data Analysis
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
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Evolving bin packing heuristics with genetic programming
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
MAGMA: a multiagent architecture for metaheuristics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Learning heuristic policies – a reinforcement learning problem
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Hyper-heuristics with low level parameter adaptation
Evolutionary Computation
A new cooperative search strategy for vehicle routing problem
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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We present a self-adaptive and distributed metaheuristic called Coalition-Based Metaheuristic (CBM). This method is based on the Agent Metaheuristic Framework (AMF) and hyper-heuristic approach. In CBM, several agents, grouped in a coalition, concurrently explore the search space of a given problem instance. Each agent modifies a solution with a set of operators. The selection of these operators is determined by heuristic rules dynamically adapted by individual and collective learning mechanisms. The intention of this study is to exploit AMF and hyper-heuristic approaches to conceive an efficient, flexible and modular metaheuristic. AMF provides a generic model of metaheuristic that encourages modularity, and hyper-heuristic approach gives some guidelines to design flexible search methods. The performance of CBM is assessed by computational experiments on the vehicle routing problem.