An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem |
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Affiliation: | 1. the Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Anhui 230031, China;2. Department of Information Management, Oriental Institute of Technology, Taiwan, ROC;3. School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Australia |
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Abstract: | This paper presents an improved fruit fly optimization algorithm (IFFOA) for solving the multidimensional knapsack problem (MKP). In IFFOA, the parallel search is employed to balance exploitation and exploration. To make full use of swarm intelligence, a modified harmony search algorithm (MHS) is proposed and applied to add cooperation among swarms in IFFOA. In MHS, novel pitch adjustment scheme and random selection rule are developed by considering specific characters of MKP and FOA. Moreover, a vertical crossover is designed to guide stagnant dimensions out of local optima and further improve the performance. Extensive numerical simulations are conducted and comparisons with other state-of-the-art algorithms verify that the proposed algorithm is an effective alternative for solving the MKP. |
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Keywords: | Multidimensional knapsack problem Fruit fly optimization algorithm Parallel search Harmony search algorithm Vertical crossover |
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