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A NNIA Scheme for Timetabling Problems

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  • Yu Lei
  • Jiao Shi

Abstract

This paper presents a memetic multiobjective optimization algorithm based on NNIA for examination timetabling problems. In this paper, the examination timetabling problem is considered as a two-objective optimization problem while it is modeled as a single-objective optimization problem generally. Within the NNIA framework, the special crossover operator is utilized to search in the solution space; two local search techniques are employed to optimize these two objectives and a diversity-keeping strategy which consists of an elitism group operator and an extension optimization operator to ensure a sufficient number of solutions in the pareto front. The proposed algorithm was tested on the most widely used uncapacitated Carter benchmarks. Experimental results prove that the proposed algorithm is a competitive algorithm.

Suggested Citation

  • Yu Lei & Jiao Shi, 2017. "A NNIA Scheme for Timetabling Problems," Journal of Optimization, Hindawi, vol. 2017, pages 1-11, May.
    • Handle: RePEc:hin:jjopti:5723239
    DOI: 10.1155/2017/5723239
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    References listed on IDEAS

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    1. Lei, Yu & Gong, Maoguo & Zhang, Jun & Li, Wei & Jiao, Licheng, 2014. "Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 234(1), pages 197-208.
    2. Massimiliano Caramia & Paolo Dell'Olmo & Giuseppe F. Italiano, 2008. "Novel Local-Search-Based Approaches to University Examination Timetabling," INFORMS Journal on Computing, INFORMS, vol. 20(1), pages 86-99, February.
    3. Burke, Edmund K. & McCollum, Barry & Meisels, Amnon & Petrovic, Sanja & Qu, Rong, 2007. "A graph-based hyper-heuristic for educational timetabling problems," European Journal of Operational Research, Elsevier, vol. 176(1), pages 177-192, January.
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