Document Type

Presentation

Publication Date

8-1-2014

Abstract

Linear, non-linear and dynamic programming, heuristics and evolutionary computation are amongst the techniques which have been applied to obtain solutions to optimal pump-scheduling problems. Most of these either greatly simplify the complex water distribution system or require significant time to solve the problem. The scheduling of pumps is frequently undertaken in near-real time, in order to minimize cost and maximize energy savings. However, this requires a computationally efficient algorithm that can rapidly identify an acceptable solution. In this paper, a hybrid optimization model is presented, coupling Linear Programming and Genetic Algorithms. The resulting hybrid optimization model has demonstrated more rapid convergence with respect to the traditional metaheuristic algorithms, whilst maintaining a good level of reliability.

Comments

Session S6-02, Special Session: Evolutionary Computing in Water Resources Planning and Management II

 
 

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