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University course timetabling using a new ecogeography-based optimization algorithm

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Abstract

As an important administrative task in the area of education, course timetabling is a complex optimization problem that is difficult to solve by conventional methods. The paper adapts a new nature-inspired metaheuristic called ecogeography-based optimization (EBO), which enhances biogeography-based optimization by equipping the population with a neighborhood structure and designing two new migration operators named global migration and local migration, to solve the university course timetabling problem (UCTP). In particular, we develop two discrete migration operators for efficiently evolving UCTP solutions based on the principle of global and local migration in EBO, and design a repair process for effectively coping with infeasible timetables. We test the discrete EBO algorithm on a set of problem instances from four universities in China, and the experimental results show that the proposed method exhibits a promising performance advantage over a number of state-of-the-art methods.

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Acknowledgments

This work is supported by National Natural Science Foundation (Grant No. 61473263) and Zhejiang Provincial Natural Science Foundation (Grant No. LY14F030011) of China.

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Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China

    Min-Xia Zhang, Bei Zhang & Neng Qian

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  1. Min-Xia Zhang
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  2. Bei Zhang
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Correspondence to Bei Zhang.

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Zhang, MX., Zhang, B. & Qian, N. University course timetabling using a new ecogeography-based optimization algorithm. Nat Comput 16, 61–74 (2017). https://doi.org/10.1007/s11047-016-9543-8

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