Evaluation of a genetic algorithm for the irrigation scheduling problem
Evaluation of a genetic algorithm for the irrigation scheduling problem
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 (N-P 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.
algorithms, irrigation scheduling, evaluation
737-744
Haq, Zia Ul
e9a57bb7-5225-45e6-9a69-2396a6e4fd31
Anwar, Arif A.
9746f367-1df2-4e0e-8d71-5ecfc9ddd000
Clarke, Derek
44762080-d8c2-4fbc-8524-0ee80d673abb
November 2008
Haq, Zia Ul
e9a57bb7-5225-45e6-9a69-2396a6e4fd31
Anwar, Arif A.
9746f367-1df2-4e0e-8d71-5ecfc9ddd000
Clarke, Derek
44762080-d8c2-4fbc-8524-0ee80d673abb
Haq, Zia Ul, Anwar, Arif A. and Clarke, Derek
(2008)
Evaluation of a genetic algorithm for the irrigation scheduling problem.
Journal of Irrigation and Drainage Engineering, ASCE, 134 (6), .
(doi:10.1061/(ASCE)0733-9437(2008)134:6(737)).
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 (N-P 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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Published date: November 2008
Additional Information:
Technical Papers
Keywords:
algorithms, irrigation scheduling, evaluation
Organisations:
Civil Engineering & the Environment
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Local EPrints ID: 75606
URI: http://eprints.soton.ac.uk/id/eprint/75606
ISSN: 0733-9437
PURE UUID: 7007cb6e-ce1a-4bff-b7f1-f3366e6c78f0
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Date deposited: 12 Mar 2010
Last modified: 14 Mar 2024 02:40
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Author:
Derek Clarke
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