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With the growing electricity demand, the likelihood of experiencing power outages is also rising. Utility companies have started buying electricity through e-auctions to address this issue. To meet the increasing electricity demand, we investigate a solution to procure energy from various sources, trading off multiple objectives while solving a complex winner(s) determination problem for resource procurement optimization. Winner determination is an NP-hard problem, and applying exact methods is impractical. Instead, we rely on nature-inspired techniques as they are appropriate for trading the quality of the returned solution for the required running time. In particular, Genetic Algorithms (GAs), Whale Optimization Algorithm (WOA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Firefly Algorithm (FA) are explored and evaluated in terms of effectiveness in producing high-quality solutions for various instances of the Combinatorial Reverse Auction (CRA) problem.

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Nature-Inspired Techniques for Combinatorial Reverse Auctions in Electricity Consumption

  • 会议论文

  • 发表日期：

    2025年

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  • Sifat E Jahan,
  • Malek Mouhoub,
  • Mehdi Sadeghilalimi

摘要

With the growing electricity demand, the likelihood of experiencing power outages is also rising. Utility companies have started buying electricity through e-auctions to address this issue. To meet the increasing electricity demand, we investigate a solution to procure energy from various sources, trading off multiple objectives while solving a complex winner(s) determination problem for resource procurement optimization. Winner determination is an NP-hard problem, and applying exact methods is impractical. Instead, we rely on nature-inspired techniques as they are appropriate for trading the quality of the returned solution for the required running time. In particular, Genetic Algorithms (GAs), Whale Optimization Algorithm (WOA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Firefly Algorithm (FA) are explored and evaluated in terms of effectiveness in producing high-quality solutions for various instances of the Combinatorial Reverse Auction (CRA) problem.