A Stochastic Hyper-Heuristic for Optimising through Comparisons

摘要：

This paper introduces a new hyper-heuristic framework for automatically searching and changing potential solutions to a particular problem. The solutions and the problem datasets are placed into a grid and then a game is played to try and optimise the total cost over the whole grid, using a randomising process. The randomisation could be compared to a simulated annealing approach, where the aim is to improve the solution space as a whole, possibly at the expense of certain better solutions. It is hoped that this will give the solution search an appropriate level of robustness to allow it to avoid local optima.

关键词： hyper-heuristic stochastic corroborative evidence genetic algorithms simulated annealing.

作者: Kieran Greer Senior Member

作者单位: Distributed Computing Systems, Belfast, UK

会议类型: 国际会议

会议名称: 2010 Third International Symposium on Knowledge Acquisition and Modeling(第三届知识获取与建模国际研讨会 KAN 2010)

会议地点: 武汉

会议语种:英文

页码: 325-328

在线出版日期: 2010-10-20（万方平台首次上网日期，不代表论文的发表时间）