Wednesday 25 Jan 2012Evolutionary Computation for Dynamic Combinatorial Optimisation Problem

Dr Shengxiang Yang - Department of Information Systems and Computing, Brunel University

Harrison 170 15:30-16:30

Evolutionary Computation (EC) encapsulates a class of stochastic optimisation algorithms, which are inspired by principles from natural and biological
evolution. EC methods have been widely used for combinatorial optimisation problems (COPs) in many fields. Traditionally, EC methods have been applied for solving static COPs. However, many real world COPs are dynamic COPs (DCOPs), which are subject to changes over time due to many factors. DCOPs pose serious challenges to traditional EC methods since they can not adapt well to a changing environment once converged. DCOPs have attracted a growing interest from the EC community in recent years due to the importance in the real-world applications of EC.

This talk will first briefly introduce the concept of DCOPs and several benchmark DCOPs for testing EC methods, then review the main approaches developed to enhance EC methods for DCOPs, and describe several detailed approaches developed for EC methods for DCOPs. After that, this talk will present a case study on EC methods for DCOPs in the real world. Finally, some conclusions will be made based on the work presented and the future work on EC for DCOPs will be briefly discussed.

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