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A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem

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  • Paul Bergey
  • Cliff Ragsdale
  • Mangesh Hoskote

Abstract

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. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Paul Bergey & Cliff Ragsdale & Mangesh Hoskote, 2003. "A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem," Annals of Operations Research, Springer, vol. 121(1), pages 33-55, July.
    • Handle: RePEc:spr:annopr:v:121:y:2003:i:1:p:33-55:10.1023/a:1023347000978
    DOI: 10.1023/A:1023347000978
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    Cited by:

    1. Yanık, Seda & Sürer, Özge & Öztayşi, Başar, 2016. "Designing sustainable energy regions using genetic algorithms and location-allocation approach," Energy, Elsevier, vol. 97(C), pages 161-172.
    2. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    3. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2021. "Solutions for districting problems with chance-constrained balancing requirements," Omega, Elsevier, vol. 103(C).
    4. Jörg Kalcsics & Stefan Nickel & Michael Schröder, 2005. "Towards a unified territorial design approach — Applications, algorithms and GIS integration," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(1), pages 1-56, June.
    5. Baghersad, Milad & Emadikhiav, Mohsen & Huang, C. Derrick & Behara, Ravi S., 2023. "Modularity maximization to design contiguous policy zones for pandemic response," European Journal of Operational Research, Elsevier, vol. 304(1), pages 99-112.
    6. Alexander Butsch & Jörg Kalcsics & Gilbert Laporte, 2014. "Districting for Arc Routing," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 809-824, November.
    7. Zhou, Xizhen & Lv, Mengqi & Ji, Yanjie & Zhang, Shuichao & Liu, Yong, 2023. "Pricing curb parking: Differentiated parking fees or cash rewards?," Transport Policy, Elsevier, vol. 142(C), pages 46-58.
    8. Sarid, Adi S. & Glynn, Peter W. & Tzur, Michal, 2024. "Power distribution in developing countries — Planning for effectiveness and equity," Omega, Elsevier, vol. 123(C).
    9. Abdul-Salam, Yakubu & Phimister, Euan, 2016. "The politico-economics of electricity planning in developing countries: A case study of Ghana," Energy Policy, Elsevier, vol. 88(C), pages 299-309.
    10. Juan A. Díaz & Dolores E. Luna, 2017. "Primal and dual bounds for the vertex p-median problem with balance constraints," Annals of Operations Research, Springer, vol. 258(2), pages 613-638, November.
    11. Camacho-Collados, M. & Liberatore, F. & Angulo, J.M., 2015. "A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector," European Journal of Operational Research, Elsevier, vol. 246(2), pages 674-684.
    12. Enzo Sauma & Fernando Traub & Jorge Vera, 2015. "A Robust optimization approach to assess the effect of delays in the connection-to-the-grid time of new generation power plants over transmission expansion planning," Annals of Operations Research, Springer, vol. 229(1), pages 703-741, June.
    13. Antonio Diglio & Stefan Nickel & Francisco Saldanha-da-Gama, 2020. "Towards a stochastic programming modeling framework for districting," Annals of Operations Research, Springer, vol. 292(1), pages 249-285, September.
    14. Trotter, Philipp A. & McManus, Marcelle C. & Maconachie, Roy, 2017. "Electricity planning and implementation in sub-Saharan Africa: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1189-1209.
    15. Fernando Tavares-Pereira & José Figueira & Vincent Mousseau & Bernard Roy, 2007. "Multiple criteria districting problems," Annals of Operations Research, Springer, vol. 154(1), pages 69-92, October.
    16. Xun-Gui Li & Xia Wei, 2008. "An Improved Genetic Algorithm-Simulated Annealing Hybrid Algorithm for the Optimization of Multiple Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(8), pages 1031-1049, August.
    17. Tavares Pereira, Fernando & Figueira, José Rui & Mousseau, Vincent & Roy, Bernard, 2009. "Comparing two territory partitions in districting problems: Indices and practical issues," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 72-88, March.

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