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A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem

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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.

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Authors and Affiliations

  1. Department of Business Management, North Carolina State University, Raleigh, NC, 27695, USA

    Paul K. Bergey

  2. Department of Business Information Technology, Virginia Tech, Blacksburg, VA, 24060, USA

    Cliff T. Ragsdale

  3. The World Bank, 1818 H Street NW, Room No. J9-027, Washington, DC, 20433, USA

    Mangesh Hoskote

Authors
  1. Paul K. Bergey
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  2. Cliff T. Ragsdale
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  3. Mangesh Hoskote
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Correspondence to Paul K. Bergey.

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Bergey, P.K., Ragsdale, C.T. & Hoskote, M. A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem. Annals of Operations Research 121, 33–55 (2003). https://doi.org/10.1023/A:1023347000978

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