The University of Southampton
University of Southampton Institutional Repository

Genetic algorithms for the sequential irrigation scheduling problem

Anwar, A.A. and Haq, Z.U. (2012) Genetic algorithms for the sequential irrigation scheduling problem Irrigation Science

Record type: Article


A sequential irrigation scheduling problem is the problem of preparing a schedule to sequentially service a set of water users. This problem has an analogy with the classical single machine earliness/tardiness scheduling problem in operations research. In previously published work, integer program and heuristics were used to solve sequential irrigation scheduling problems; however, such scheduling problems belong to a class of combinatorial optimization problems known to be computationally demanding (NP-hard). This is widely reported in operations research. Hence, integer program 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 (GA), simulated annealing, or tabu search methods need to be used. These need to be formulated carefully and tested thoroughly. The current research is to explore the potential of GA to solve the sequential irrigation scheduling problems. Four GA models are presented that model four different sequential irrigation scenarios. The GA models are tested extensively for a range of problem sizes, and the solution quality is compared against solutions from integer programs and heuristics. The GA is applied to the practical engineering problem of scheduling
water scheduling to 94 water users.

Full text not available from this repository.

More information

e-pub ahead of print date: 24 July 2012
Organisations: Energy & Climate Change Group


Local EPrints ID: 343630
ISSN: 0342-7188
PURE UUID: 2cc7ebec-108f-4354-af59-93c39ddd4565

Catalogue record

Date deposited: 09 Oct 2012 11:29
Last modified: 18 Jul 2017 05:21

Export record


Author: A.A. Anwar
Author: Z.U. Haq

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.