{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T21:10:17Z","timestamp":1768511417117,"version":"3.49.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>Multifactorial evolutionary algorithm (MFEA) exploits the parallelism of population-based evolutionaryalgorithm and provides an efficient way to evolve individuals for solving multiple tasks concurrently.Its efficiency is derived by implicitly transferring the genetic information among tasks.However, MFEA doesn?t distinguish the information quality in the transfer compromising the algorithmperformance. We propose a group-based MFEA that groups tasks of similar types and selectivelytransfers the genetic information only within the groups. We also develop a new selection criterionand an additional mating selection mechanism in order to strengthen the effectiveness andefficiency of the improved MFEA. We conduct the experiments in both the cross-domain and intra-domainproblems.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/538","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"3870-3876","source":"Crossref","is-referenced-by-count":69,"title":["A Group-based Approach to Improve Multifactorial Evolutionary Algorithm"],"prefix":"10.24963","author":[{"given":"Jing","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Computer Science & Information Systems, Teesside University, UK"}]},{"given":"Yingke","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Information Systems, Teesside University, UK"}]},{"given":"Zixuan","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Computer Science & Engineering, University of Electronic Science and Technology of China, China"}]},{"given":"Yanping","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Computer Science & Engineering, University of Electronic Science and Technology of China, China"}]},{"given":"Colin","family":"Paul Joy","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Information Systems, Teesside University, UK"}]}],"member":"10584","event":{"name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","theme":"Artificial Intelligence","location":"Stockholm, Sweden","acronym":"IJCAI-2018","number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2018,7,13]]},"end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:53:45Z","timestamp":1530755625000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/538"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/538","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}