{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T17:54:11Z","timestamp":1785434051275,"version":"3.56.0"},"reference-count":40,"publisher":"Cambridge University Press (CUP)","issue":"4","license":[{"start":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T00:00:00Z","timestamp":1780963200000},"content-version":"unspecified","delay-in-days":69,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>To overcome the limitations of conventional robot task allocation algorithms, which often converge to suboptimal solutions, suffer from low computational accuracy, and produce excessively long execution paths as problem scales increase, we propose a novel marine predator algorithm (NMPA). By redesigning the predator\u2013prey encoding mechanism in the traditional marine predator algorithm (MPA) and integrating information-based environmental search strategies with local search techniques, the proposed method substantially improves global exploration capability and solution precision. The NMPA is then evaluated on multiple benchmark and practical scenarios, including the traveling salesman problem (TSP), multi-traveling salesman problem (MTSP), single-robot task allocation with rigid time windows, and multi-robot task allocation. Experimental results on TSP and MTSP indicate that NMPA achieves more stable convergence, higher accuracy, and stronger robustness than ant colony optimization (ACO), simulated annealing, genetic algorithms (GAs), and their variants. Moreover, validation on real-world factory data in both single-robot and multi-robot task allocation scenarios confirms that NMPA delivers superior solution quality and overall performance compared with ACO, GAs, and their variants.<\/jats:p>","DOI":"10.1017\/s0263574726103531","type":"journal-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T07:42:43Z","timestamp":1780990963000},"page":"1179-1211","source":"Crossref","is-referenced-by-count":0,"title":["A novel marine predator algorithm for robot task allocation problem"],"prefix":"10.1017","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3457-7951","authenticated-orcid":false,"given":"Xuefeng","family":"Gao","sequence":"first","affiliation":[{"name":"School of Instrumentation Science and Opto-Electronics Engineering, Beijing Information Science and Technology University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junkai","family":"Yi","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xnqep60","id-type":"ROR","asserted-by":"publisher"}],"name":"College of Computer Science, Beijing Information Science and Technology University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongyue","family":"Wang","sequence":"additional","affiliation":[{"name":"Jiangsu Shuguang Optoelectronics Co., Ltd."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Information Science and Technology University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingling","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Information Science and Technology University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Liu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xnqep60","id-type":"ROR","asserted-by":"publisher"}],"name":"College of Computer Science, Beijing Information Science and Technology University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2026,6,9]]},"reference":[{"key":"S0263574726103531_ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-09726-3_5"},{"key":"S0263574726103531_ref37","doi-asserted-by":"publisher","DOI":"10.1109\/YAC.2018.8406459"},{"key":"S0263574726103531_ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.108653"},{"key":"S0263574726103531_ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05468-4"},{"key":"S0263574726103531_ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107598"},{"key":"S0263574726103531_ref5","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574725101914"},{"key":"S0263574726103531_ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2025.3546281"},{"key":"S0263574726103531_ref8","volume-title":"Operations Research: Applications and Algorithm","author":"Winston","year":"2004"},{"key":"S0263574726103531_ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-021-05688-3"},{"key":"S0263574726103531_ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2022.104314"},{"key":"S0263574726103531_ref29","unstructured":"[29] Colorni, A. , Dorigo, M. , Maniezzo, V. ,\u00a0\u201cDistributed Optimization by Ant Colonies,\u201d In: Proceedings of the First European Conference on Artificial Life , vol. 142 (Paris, France, 1991) pp. 134\u2013142."},{"key":"S0263574726103531_ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s40745-021-00354-9"},{"key":"S0263574726103531_ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107467"},{"key":"S0263574726103531_ref39","first-page":"65","article-title":"Modification of the ant colony optimization for solving the multiple traveling salesman problem","volume":"16","author":"Yousefikhoshbakht","year":"2013","journal-title":"Rom. 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