Evaluation of a Genetic Algorithm for the Irrigation Scheduling Problem
Publication: Journal of Irrigation and Drainage Engineering
Volume 134, Issue 6
Abstract
A typical irrigation scheduling problem is one of preparing a schedule to service a group of outlets which may be serviced simultaneously. This problem has an analogy with the classical earliness/tardiness problem in operations research. In previously published work an integer program was used to solve this problem, however such scheduling problems belong to a class of combinatorial problems known to be computationally demanding ( hard). This is widely reported in operations research. Hence integer programs can only be used to solve relatively small problems usually in a research environment where considerable computational resources and time can be allocated to solve a single schedule. For practical applications metaheuristics such as genetic algorithms, simulated annealing, or tabu search methods need to be used. However as reported in the literature, these need to be formulated carefully and tested thoroughly. This paper demonstrates the importance of robust testing of one such genetic algorithm formulated to solve the irrigation scheduling problem with simultaneous outlets serviced against an integer program formulated to solve the same problem.
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Acknowledgments
The writers wish to acknowledge the contribution of Kristin Welter to this work who carried out some of the early coding of the reimplemented GA and some of the computational experiments.
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© 2008 ASCE.
History
Received: May 4, 2007
Accepted: Mar 11, 2008
Published online: Dec 1, 2008
Published in print: Dec 2008
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