Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Blackboard systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Asynchronous Teams: Cooperation Schemes for Autonomous Agents
Journal of Heuristics
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Agent-Oriented Model of Simulated Evolution
SOFSEM '02 Proceedings of the 29th Conference on Current Trends in Theory and Practice of Informatics: Theory and Practice of Informatics
Ant Colony Optimization
The parameter-less genetic algorithm in practice
Information Sciences—Informatics and Computer Science: An International Journal
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Genetic programming: optimal population sizes for varying complexity problems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
JADE-Based A-Team as a Tool for Implementing Population-Based Algorithms
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 03
Explicit and Emergent Cooperation Schemes for Search Algorithms
Learning and Intelligent Optimization
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ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
A model of co-evolution in multi-agent system
CEEMAS'03 Proceedings of the 3rd Central and Eastern European conference on Multi-agent systems
Hybrid Metaheuristics: An Emerging Approach to Optimization
Hybrid Metaheuristics: An Emerging Approach to Optimization
JABAT middleware as a tool for solving optimization problems
Transactions on computational collective intelligence II
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
A new adaptive multi-start technique for combinatorial global optimizations
Operations Research Letters
IEEE Transactions on Neural Networks
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Usually a lot of experiments are often required in order to tune population-based algorithms, designed for solving difficult optimization problems. Individial features of a particular problem, different parameters of population of individuals, or structure of the algorithm may influence results produced by the system. The paper aims at evaluating experimentally to what extent (if any) different values of the population parameters controlled by the user in a multi-agent system solving instances of Vehicle Routing Problem influence computational results. The reported experiment involved several methods of creating an initial population of solutions and several cooperating agents representing improvement heuristics working in parallel.