A New Genetic Algorithm for Multiple-Choice Multidimensional Knapsack Problem | ||||
| The International Conference on Electrical Engineering | ||||
| Article 77, Volume 7, 7th International Conference on Electrical Engineering ICEENG 2010, May 2010, Page 1-17 PDF (191.17 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iceeng.2010.33055 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| A. F. Heikal1; M. H. Rasmy2; A. A. Tharwat2; M. A. El-Beltagy2 | ||||
| 1Egyptian Armed Forces. | ||||
| 2Faculty of Computers and Information, Cairo University, Cairo, Egypt. | ||||
| Abstract | ||||
| Abstract: A New Genetic Algorithm (NGA) for solving the Multiple Choice Multidimensional Knapsack Problem (MMKP) is presented in this paper. The MMKP can be applied to solve a wide variety of real life problems i.e., in any area where tasks must be scheduled or budgeted. This paper introduces NGA algorithm that hybridize the solution construction mechanism of GA operators (hybrid selection operator, hybrid cross-over operator and new hybrid mutation operator) for permutation encoding genetic algorithm. In addition we present a strong initial population is created by the Maximizing Value per Resources Consumption (MVRC) heuristic algorithm. The experimental results show that the method is very efficient and competitive to solve the MMKP compared with the better existing methods | ||||
| Keywords | ||||
| Genetic Algorithm; MMKP; MVRC; Heuristic Algorithms | ||||
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