1997 Fiscal Year Final Research Report Summary
Multi-objective Optimization for Location/Allocation Planning of Networked Facilities Using Genetic Algorithm
| Project/Area Number |
08680459
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
社会システム工学
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| Research Institution | TOYOHASHI UNIVERSITY OF TECHNOLOGY (1997)
Kyoto University (1996) |
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Principal Investigator |
SHIMIZU Yoshiaki TOYOHASHI UNIVERSITY OF TECHNOLOGY,ENGINEERING,PROFESSOR, 工学部, 教授 (10109085)
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| Project Period (FY) |
1996 – 1997
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| Keywords | Multi-objective optimization / Site location / allocation planning / Mixed-integer programs / Genetic algorithm / Progressive linear programs / Neural network / Waste disposal planning |
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| Research Abstract |
Taking importance of developing flexible optimization methods managing conflict resolution in mind, we have concerned with site location problems under multi-objectives. As known from the term NIMBY (Not In My Back Yard), the site location problem of hazardous wastes is an eligible case study for such a situation, that is to say, associated with all human, environmental and economic concerns.
First backgrounds of the site-location problems have been investigated broadly, and presented some kinds of typical formulation with a few examples. Then we have formulated the problem generally as multi-objective mixed-integer programs (MOMIP). For this, we have proposed an intelligence supported approach incorporating a hybrid use of genetic algorithm (GA) with mathematical program, and neural networks (NN) for value function modeling. To improve the performance of the mathematical program referred to the linear programming presently, at the stage of program implementation, we applied the progressive linear program developed by the author.
Furthermore, concerned with the solution of multi-objective GA particularly, we have introduced a new genetic operation named repair operation to improve performance. From practical points of view, we also considered it very important to provide an approach reflecting certain qualitative aspects imbedded in real-world problem-solving. Concerning with this, we have shown the present approach can deal with such like situation very suitably.
By taking an example in waste disposal site planning problem, which was formulated as a mixed-integer linear program (MILP), we have examined the effectiveness of proposed approach from every aspect concerned here numerically.
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