A simulated annealing genetic algorithm for the electrical power districting problem

被引：54

作者：

Bergey, PK ^{[1
]}

Ragsdale, CT

Hoskote, M

机构：

[1] N Carolina State Univ, Dept Business Management, Raleigh, NC 27695 USA

[2] Virginia Tech, Dept Business Informat Technol, Blacksburg, VA 24060 USA

[3] World Bank, Washington, DC 20433 USA

来源：

ANNALS OF OPERATIONS RESEARCH | 2003年 / 121卷 / 1-4期

关键词：

electricity deregulation; genetic algorithms; simulated annealing; multi-criteria decision making;

D O I：

10.1023/A:1023347000978

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

Due to a variety of political, economic, and technological factors, many national electricity industries around the globe are transforming from non-competitive monopolies with centralized systems to decentralized operations with competitive business units. A key challenge faced by energy restructuring specialists at the World Bank is trying to simultaneously optimize the various criteria one can use to judge the fairness and commercial viability of a particular power districting plan. This research introduces and tests a new algorithm for solving the electrical power districting problem in the context of the Republic of Ghana and using a random test problem generator. We show that our mimetic algorithm, the Simulated Annealing Genetic Algorithm, outperforms a well-known Parallel Simulated Annealing heuristic on this new and interesting problem manifested by the deregulation of electricity markets.

引用

页码：33 / 55

页数：23

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