{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T21:22:52Z","timestamp":1774300972221,"version":"3.50.1"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":52,"publisher":"Elsevier BV","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Finding the optimal sequence of switching operations to reconfigure a power distribution system is a complex combinatorial problem critical for minimizing transient negative impacts. To address this challenge, this paper introduces a Specialized Tabu Search (STS) algorithm and hybridizes it with a novel heuristic preprocessing framework for search space reduction. Three distinct pairing strategies are proposed for this framework, representing a spectrum from a conservative, mutually exclusive rule to a highly opportunistic iterative approach. To rigorously validate the proposed STS-based method, its performance is benchmarked against Variable Neighborhood Search (VNS) variants, which serve as a powerful benchmark. All methods are evaluated on five benchmark systems (16- to 417-node), analyzing the impact of each pairing strategy on both the STS and VNS frameworks. Results demonstrate that pairing heuristics can significantly accelerate convergence, but the optimal strategy depends on a critical trade-off. Conservative heuristics prove essential for navigating complex search landscapes with deceptive optima, whereas more aggressive strategies offer the fastest convergence on well-behaved problems. This work not only establishes the STS as a viable method for the OSS-DSR problem but also provides a clear, evidence-based guide on the synergistic effects of combining different levels of heuristic guidance with distinct metaheuristics.<\/jats:p>","DOI":"10.2139\/ssrn.6460561","type":"posted-content","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T20:37:54Z","timestamp":1774298274000},"source":"Crossref","is-referenced-by-count":0,"title":["Heuristic-Accelerated Metaheuristics for the Optimal Switching Sequence Problem in Distribution Systems Reconfiguration"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7934-1910","authenticated-orcid":true,"given":"Rafael Y.","family":"Yamamoto","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7744-254X","authenticated-orcid":true,"given":"Rub\u00e9n","family":"Romero","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9178-0601","authenticated-orcid":true,"given":"Leonardo  H.","family":"Macedo","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"6","key":"ref1","article-title":"A novel solution method for the distribution network reconfiguration problem based on a search mechanism enhancement of the improved harmony search algorithm","volume":"15","author":"J D Santos","year":"2022","journal-title":"Energies"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1007\/s40313-018-0415-6","article-title":"A contribution to the optimization of the reconfiguration problem in radial distribution systems","volume":"29","author":"L H Macedo","year":"2018","journal-title":"Journal of Control, Automation 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Mantovani","year":"2000","journal-title":"Revista Brasileira de Controle & Automa\ufffd\ufffdo -SBA"},{"key":"ref40","volume":"20","author":"B Table","journal-title":"Best-Found Solution Sequences for the 417-Node System"},{"key":"ref41","journal-title":"Method Best-Found Solution"},{"key":"ref42","volume":"42","journal-title":"Initial Solution"},{"key":"ref43","volume":"22","author":"Vnd + S","year":"1922"},{"key":"ref44","volume":"58","author":"Vnd + S","year":"0330"},{"key":"ref45","volume":"29","author":"Sts + S","year":"2008"},{"key":"ref46","volume":"33","author":"Sts + S","year":"2018"},{"key":"ref47","volume":"22","author":"Sts + S","year":"1922"},{"key":"ref48","volume":"59","author":"Sts + S","year":"0318"},{"key":"ref49","volume":"33","author":"Bvns + S","year":"2011"},{"key":"ref50","volume":"26","author":"Bvns + S","year":"1922"},{"key":"ref51","volume":"7","author":"Bvns + S"},{"key":"ref52","article-title":"His research interests include the theory and application of metaheuristics, optimization and planning of power distribution and transmission systems, mathematical modeling, and artificial intelligence applied to power system data forecasting. Rub\ufffdn Romero received the B.S. and P.E. degrees in electrical engineering from the National University of Engineering","author":"Un-Esp)","year":"1978","journal-title":"His research interests include methods for the optimization, planning, and control of electrical power systems, applications of artificial intelligence in power systems, and operations research. Leonardo H. Macedo received the B.S., M.S., and Ph.D. degrees, all in electrical engineering"}],"container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T20:40:33Z","timestamp":1774298433000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=6460561"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":52,"URL":"https:\/\/doi.org\/10.2139\/ssrn.6460561","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}