Zbigniew Skolicki
ABSTRACT
A need for solving more and more complex problems drives the Evolutionary Computation community towards advanced models of Evolutionary Algorithms. One such model is the island model which, although the subject of a variety of studies, still needs additional fundamental research. In my Ph.D. thesis I am aiming at studying the behavior of island models with regard to the amount of cooperation between islands, the level of heterogeneity and the difficulty of the problem being solved. This paper presents the main ideas and gathers preliminary results.
- E. Alba and J. M. Troya. An analysis of synchronous and asynchronous parallel distributed genetic algorithms with structured and panmictic islands. In IPPS/SPDP Workshops, pages 248--256, 1999. Google Scholar
Digital Library
- L. Barbulescu, J.-P. Watson, and D. Whitley. Dynamic representations and escaping local optima: Improving genetic algorithms and local search. In AAAI/IAAI, pages 879--884, 2000. Google ScholarDigital Library
- J. Branke, A. Kamper, and H. Schmeck. Distribution of evolutionary algorithms in heterogeneous networks. In Proceedings of Genetic and Evolutionary Computation Conference - GECCO 2004. Springer-Verlag, 2004.Google ScholarCross Ref
- E. Cantú-Paz. Efficient and Accurate Parallel Genetic Algorithms. Kluwer Academic Publishers, 2000. Google ScholarDigital Library
- D. Eby, R. Averill, E. Goodman, and W. Punch. The optimization of flywheels using an injection island genetic algorithm. In P. Bentley, editor, Evolutionary Design by Computers, pages 167--190. Morgan Kaufmann, San Francisco, 1999.Google Scholar
- F. Fernández, M. Tomassini, and L. Vanneschi. An empirical study of multipopulation genetic programming. Genetic Programming and Evolvable Machines, 4(1):21--51, March 2003. Google ScholarDigital Library
- S. M. Gustafson. An Analysis of Diversity in Genetic Programming. PhD thesis, The University of Nottingham, 2004.Google Scholar
- J. Hu and E. Goodman. The hierarchical fair competition model for parallel evolutionary algorithms. In Congress of Evolutionary Computation, CEC 2002, IEEE World Congress on Computational Intelligence, 2002.Google Scholar
- G. Rudolph. On takeover times in spatially structured populations: Array and ring. In K. K. Lai, O. Katai, M. Gen, and B. Lin, editors, Proceedings of theSecondAsia-Pacific Conference on Genetic Algorithms and Applications(APGA '00), pages 144--151, Hong Kong, PR China, 2000. Global-Link Publishing Company.Google Scholar
- Z. Skolicki and K. De Jong. Improving evolutionary algorithms with multi-representation island models. In Parallel Problem Solving from Nature -- PPSN VIII 8th International Conference. Springer-Verlag, 2004.Google Scholar
- Z. Skolicki and K. De Jong. The influence of migration sizes and intervals on island models. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005). ACM Press, 2005. Google ScholarDigital Library
- M. Toussaint and C. Igel. Neutrality: A necessity for self-adaptation. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), pages 1354--1359, 2002. Google ScholarDigital Library
- R. K. Ursem. Models for Evolutionary Algorithms and Their Applications in System Identification and Control Optimization. PhD thesis, University of Aarhus, EVALife, Dept. of Computer Science, Denmark, 2003.Google Scholar
- D. Whitley, S. Rana, and R. B. Heckendorn. The island model genetic algorithm: On separability, population size and convergence. Journal of Computing and Information Technology, 7(1):33--47, 1999.Google Scholar
Index Terms
- An analysis of island models in evolutionary computation
Recommendations
Analysis of evolutionary multi-tasking as an island model
GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference CompanionRecently, an idea of evolutionary multi-tasking has been proposed and applied to various types of optimization problems. The basic idea of evolutionary multi-tasking is to simultaneously solve multiple optimization problems (i.e., tasks) in a ...
The influence of migration sizes and intervals on island models
GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computationA need for solving more and more complex problems drives the Evolutionary Computation community towards advanced models of Evolutionary Algorithms. One such model is the island model which, although the subject of a variety of studies, still needs ...
An effective new island model genetic algorithm for job shop scheduling problem
This paper presents an effective new island model genetic algorithm to solve the well-known job shop scheduling problem with the objective of minimizing the makespan. To improve the effectiveness of the classical island model genetic algorithm, we have ...
Comments