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Design for a Novel Framework of hyper-heuristic Algorithm

Journal of Donghua University(English Edition) 2014年第2期31卷 109-112页

作者：郭为安汪镭陈明刘晋飞吴启迪 Sino-German College of Applied Sciences Tongji University School of Electronics and Information Tongji University

A novel framework of hyper-heuristic algorithm was proposed to improve the adaption of evolutionary algorithms( EAs)in optimization. The algorithm could be changed during the evolutionary progress according to their performances. In addition,a large number of elite individuals were employed in the algorithm and the elite individuals helped algorithm achieve a better performance,while such number of elite individuals stagnated the global convergence in conventional single algorithm. The time complexity was analyzed to demonstrate the novel framework did not increase the time complexity. The simulation results indicate that the proposed framework outperforms any single algorithm that composes the framework.

关键词： hyper-heuristic algorithm adaption elite individuals evolutionary algorithm time complexity

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A memetic algorithm based on hyper-heuristics for examination timetabling problems

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International Journal of Intelligent Computing and Cybernetics 2015年第2期8卷 139-151页

作者： Yu Lei Maoguo Gong Licheng Jiao Yi Zuo Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education International Research Center for Intelligent Perception and ComputationXidian UniversityXi’anChina

Purpose–The examination timetabling problem is an NP-hard problem.A large number of approaches for this problem are developed to find more appropriate search ***-heuristic is a kind of representative *** hyper-heuristic,the high-level search is executed to construct heuristic lists by traditional methods(such as Tabu search,variable neighborhoods and so on).The purpose of this paper is to apply the evolutionary strategy instead of traditional methods for high-level search to improve the capability of global ***/methodology/approach–This paper combines hyper-heuristic with evolutionary strategy to solve examination timetabling ***,four graph coloring heuristics are employed to construct heuristic *** the evolutionary algorithm framework,the iterative initialization is utilized to improve the number of feasible solutions in the population;meanwhile,the crossover and mutation operators are applied to find potential heuristic lists in the heuristic space(high-level search).At last,two local search methods are combined to optimize the feasible solutions in the solution space(low-level search).Findings–Experimental results demonstrate that the proposed approach obtains competitive results and outperforms the compared approaches on some benchmark ***/value–The contribution of this paper is the development of a framework which combines evolutionary algorithm and hyper-heuristic for examination timetabling problems.

关键词： Evolutionary computation Examination timetabling problem hyper-heuristic Memetic algorithm

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