{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:36:05Z","timestamp":1761176165424,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>We introduce the Multi-Objective Combinatorial Reconfiguration Optimization Problem (MO-CROP), and propose an Answer Set Programming (ASP) based approach for its solution. MO-CROP involves finding the Pareto-optimal sequences (or Pareto front) of adjacent feasible solutions between two given feasible solutions of a combinatorial problem, considering both cost and length. Our algorithm is compactly implemented through multi-shot ASP solving, and its implementing solver optirecon provides an effective tool for solving MO-CROP. As a concrete example of MO-CROP, we present an ASP encoding for solving the multi-objective independent set reconfiguration optimization problem. Experimental results on the benchmark set from the recent CoRe Challenge demonstrate our approach\u2019s ability to capture diverse optimal sequences that reveal trade-offs between cost and length, a capability often lacking in traditional combinatorial reconfiguration methods.<\/jats:p>","DOI":"10.3233\/faia250982","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:47:45Z","timestamp":1761126465000},"source":"Crossref","is-referenced-by-count":0,"title":["Multi-Objective Combinatorial Reconfiguration Considering Cost and Length by Answer Set Programming: Algorithms, Encodings, and Empirical Analysis"],"prefix":"10.3233","author":[{"given":"Kazuki","family":"Takada","sequence":"first","affiliation":[{"name":"Nagoya University, Japan"}]},{"given":"Mutsunori","family":"Banbara","sequence":"additional","affiliation":[{"name":"Nagoya University, Japan"}]},{"given":"Takehiro","family":"Ito","sequence":"additional","affiliation":[{"name":"Graduate School of Information Sciences, Tohoku University, Japan"}]},{"given":"Jun","family":"Kawahara","sequence":"additional","affiliation":[{"name":"Kyoto University, Japan"}]},{"given":"Shin-ichi","family":"Minato","sequence":"additional","affiliation":[{"name":"Kyoto University, Japan"}]},{"given":"Torsten","family":"Schaub","sequence":"additional","affiliation":[{"name":"University of Potsdam, Germany"}]},{"given":"Ryuhei","family":"Uehara","sequence":"additional","affiliation":[{"name":"Japan Advanced Institute of Science and Technology, Japan"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:47:45Z","timestamp":1761126465000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250982"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250982","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}