Optimizing scheduling problem using an estimation of distribution algorithm and genetic algorithm

Jiang Qun; Ou Yang; Shi-Du Dong

doi:10.1117/12.784011

9 January 2008 Optimizing scheduling problem using an estimation of distribution algorithm and genetic algorithm

Jiang Qun, Ou Yang, Shi-Du Dong

Proceedings Volume 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials; 67943Y (2008) https://doi.org/10.1117/12.784011
Event: ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 2007, Gifu, Japan

Abstract

This paper presents a methodology for using heuristic search methods to optimize scheduling problem. Specifically, an Estimation of Distribution Algorithm (EDA)- Population Based Incremental Learning (PBIL), and Genetic Algorithm (GA) have been applied to finding effective arrangement of curriculum schedule of Universities. To our knowledge, EDAs have been applied to fewer real world problems compared to GAs, and the goal of the present paper is to expand the application domain of this technique. The experimental results indicate a good applicability of PBIL to optimize scheduling problem.

Citation Download Citation

Jiang Qun, Ou Yang, and Shi-Du Dong "Optimizing scheduling problem using an estimation of distribution algorithm and genetic algorithm", Proc. SPIE 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 67943Y (9 January 2008); https://doi.org/10.1117/12.784011

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