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Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems

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Abstract

Recently, there has been an increasing effort to address integrated problems that are composed of multiple interrelated sub-problems. Many integrated problems in the real world have a multileveled structure. This paper proposes a new method of solving integrated and multileveled problems. The proposed method is named Multileveled Symbiotic Evolutionary Algorithm (MSEA). MSEA is an evolutionary algorithm that imitates the process of symbiotic evolution, including endosymbiotic evolution. It is designed to promote the balance of population diversity and population convergence. To verify its applicability, MSEA is applied to loading problems of flexible manufacturing systems with various flexibilities. Through computer experiments, the features of MSEA are shown and their effects on search capability are discussed. The proposed algorithm is also compared with existing ones in terms of solution quality. The experimental results confirm the effectiveness of our approach.

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Authors and Affiliations

  1. School of Business Administration, Chonnam National University, Gwangju, 500-757, Republic of Korea

    Jae Yun Kim

  2. Department of Industrial Engineering, Chonnam National University, 300 Yongbongdong, Bukgu, Gwangju, 500-757, Republic of Korea

    Yeo Keun Kim

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  1. Jae Yun Kim
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  2. Yeo Keun Kim
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Correspondence to Jae Yun Kim.

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Kim, J.Y., Kim, Y.K. Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems. Appl Intell 22, 233–249 (2005). https://doi.org/10.1007/s10791-005-6621-4

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