A genetic algorithm approach for solving the daily photograph selection problem of the SPOT5 satellite |
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| Authors: | Mohamed AA Mansour Maged M Dessouky |
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| Affiliation: | 1. Industrial Engineering Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt;2. Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089-0193, United States;1. Institut für Neurophysiologie, Medizinische Hochschule Hannover, Hannover, Germany;1. Institute of Electronic and Information, Hangzhou Dianzi University, Hangzhou, PR China;2. School of Electronic and Information Engineering, Tianjin University, Tianjin, PR China;3. Brigates Microelectronics Co., Ltd., Kunshan, PR China;1. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;2. School of Aerospace, Tsinghua University, Beijing 100084, China |
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| Abstract: | This article addresses the combinatorial optimization problem of managing earth observation satellites (EOSs) such as the French SPOT5, which is concerned with selecting on each day a subset of a set of candidate photographs. The problem has a significant economic importance due to its high initial investment cost that exists in these instruments and its solution difficulty resulting from the large solution space, making it an attractive research area. This article proposes a genetic algorithm (GA) for solving the SPOT5 selection problem using a new genome representation for maximizing not only a single objective as profit but a multi-criteria objective that includes the number of acquired photographs. Test results of our proposed GA show that it finds optimal solutions effectively for moderate size problems and obtains better results for two large benchmark instances coded 1403 and 1504 in the literature. Also, we verify the result that the best known value in the literature for problem coded 1401 is an optimal value. |
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