| Hybrid heuristic and mathematical programming in oil pipelines networks： Use of immigrants |
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| 作者姓名： | DELACRUZJ.M. HERRAN-GONZALEZA. RISCO-MARTINJ.L. ANDRES-TOROB. |
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| 作者单位： | Department of Computer Architecture and Automatic Control，Complutense University of Madrid，28040 Madrid，Spain，Department of Computer Architecture and Automatic Control，Complutense University of Madrid，28040 Madrid，Spain，Department of Computer Science Engineering，C.E.S. Felipe II (U.C.M.)，28300 Aranjuez，Spain，Department of Computer Architecture and Automatic Control，Complutense University of Madrid，28040 Madrid，Spain |
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| 摘 要： | We solve the problem of petroleum products distribution through oil pipelines networks. This problem is modelled and solved using two techniques: A heuristic method like a multiobjective evolutionary algorithm and Mathematical Programming. In the multiobjective evolutionary algorithm, several objective functions are defined to express the goals of the solutions as well as the preferences among them. Some constraints are included as hard objective functions and some are evaluated through a …
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| 关 键 词： | 石油输送 石油管道 数学模型 程序设计 |
Hybrid heuristic and mathematical programming in oil pipelines networks: Use of immigrants |
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| DELACRUZJ.M. HERRAN-GONZALEZA. RISCO-MARTINJ.L. ANDRES-TOROB..Hybrid heuristic and mathematical programming in oil pipelines networks: Use of immigrants[J].Journal of Zhejiang University Science,2005,6(1):9-19. |
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| Authors: | J M De La Cruz A Herrán-González J L Risco-Martín B Andrés-Toro |
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| Institution: | (1) Department of Computer Architecture and Automatic Control, Complutense University of Madrid, 28040 Madrid, Spain;(2) Department of Computer Science Engineering, C.E.S. Felipe II (U.C.M.), 28300 Aranjuez, Spain |
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| Abstract: | We solve the problem of petroleum products distribution through oil pipelines networks. This problem is modelled and solved using two techniques: A heuristic method like a multiobjective evolutionary algorithm and Mathematical Programming. In the multiobjective evolutionary algorithm, several objective functions are defined to express the goals of the solutions as well as the preferences among them. Some constraints are included as hard objective functions and some are evaluated through a repairing function to avoid infeasible solutions. In the Mathematical Programming approach the multiobjective optimization is solved using the Constraint Method in Mixed Integer Linear Programming. Some constraints of the mathematical model are nonlinear, so they are linearized. The results obtained with both methods for one concrete network are presented. They are compared with a hybrid solution, where we use the results obtained by Mathematical Programming as the seed of the evolutionary algorithm. |
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| Keywords: | MOEA MILP Hybrid algorithm Constraints |
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