Comparative analysis of Simulated Annealing, Simulated Quenching and Genetic Algorithms for optimal reservoir operation

被引：75

作者：

Vasan, A. ^{[1
]}

Raju, Komaragiri Srinivasa ^{[2
]}

机构：

[1] Univ Western Ontario, Dept Civil & Environm Engn, London, ON N6A 5B9, Canada

[2] Birla Inst Technol & Sci, Civil Engn Grp, Pilani 333031, Rajasthan, India

来源：

APPLIED SOFT COMPUTING | 2009年 / 9卷 / 01期

关键词：

Genetic Algorithms; Simulated Annealing; Simulated Quenching; Irrigation planning; India; OPTIMIZATION; GROUNDWATER;

D O I：

10.1016/j.asoc.2007.09.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The present study deals with the application of non-traditional optimization techniques, namely, Simulated Annealing (SA), Simulated Quenching (SQ) and Real-coded Genetic Algorithms (RGA) to a case study of Mahi Bajaj Sagar Project, India. The objective of the study is to maximize the annual net benefits subjected to various irrigation planning constraints for 75% dependable flow scenario. Extensive sensitivity analysis on various parameters used in above techniques indicated that they yielded same solution corresponding to a set of optimal combination of parameters. It is concluded that SA, SQ and RGA can be utilized for efficient planning of any irrigation system with suitable modi. cations. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：274 / 281

页数：8

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