¹Institute of Computer Network System, Hefei University of Technology, Hefei City, China
²School of Management, Hefei University of Technology, Hefei City, China
³School of Business, Jiujiang University, Jiujiang City, China
⁴School of Information Science and Technology, Jiujiang University, Jiujiang City, China

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Abstract—Differential Evolution is a competive method for continuous number optimization problems. A novel Structure-Encoding Differential Evolution (SEDE) algorithm was proposed for optimization problems with integer-parameter representation. In the SEDE Algorithm, each decision variable of every individual consists of two domains. One domain is float-encoding which is confined in a narrow range [0, 1]. The other domain is integer-encoding which is used to represent the problem space. A new operator, boundary-handling operator, was used to ensure each result generated by the mutation operator falling into the range [0, 1]. In addition, a new mapping operator was constructed to generate integer number from the real domain. The global convergence property of the SEDE was analyzed. The simulation results of several Benchmarks of integer programming show it is effective and efficient. Structure-encoding Differential Evolution algorithm is a new effective way for handling the integer programming problems.

Index Terms—Integer Programming, Structure-encoding Differential Evolution, boundary-handling operator, mapping operator

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Cite: Changshou Deng, Changyong Liang, Bingyan Zhao, Yanlin Yang, Anyuan Deng, "Structure-Encoding Differential Evolution for Integer Programming," Journal of Software vol. 6, no. 1, pp. 140-147, 2011.