{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T03:00:54Z","timestamp":1777086054872,"version":"3.51.4"},"reference-count":57,"publisher":"Institution of Engineering and Technology (IET)","issue":"6","license":[{"start":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T00:00:00Z","timestamp":1660262400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["ietresearch.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["IET Software"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The optimal requirements selection set aims primarily at careful search for the best requirements set of the next release of software during development process. This procedure is widely defined as the next release problem (NRP), which is also classified as NP\u2010hard dilemma. Several techniques, in literature, have been proposed to tackle NRP. However, in real examples, the earlier studies still immature as NRP still suffers interactions and restrictions that makes the problem more complicated. Although few interesting works have been presented, yet NRP, based on our study, could be further investigated and effectively tackled. In this research, therefore, NRP is devised as a multi\u2010objective optimisation problem. Two clashing objectives (satisfaction and cost) and two constraints (interactions forms) are formulated. To tackle NRP effectively, a new hybrid genetic and artificial bee colony algorithm (HGABC) is introduced. HGABC combines features of genetic and artificial bee colony algorithms. Experimental study, using case studies and three criteria, have been conducted to show HGABC's power of generating non\u2010dominated effective Pareto solutions versus the state\u2010of\u2010the\u2010art algorithms. Results indicate that HGABC does not just outperform its rivals, yet\u00a0also gives better Pareto solutions in terms of diversity and quality for almost all the instances of this problem.<\/jats:p>","DOI":"10.1049\/sfw2.12070","type":"journal-article","created":{"date-parts":[[2022,8,13]],"date-time":"2022-08-13T00:45:15Z","timestamp":1660351515000},"page":"558-575","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Software requirement selection using a combined multi\u2010objective optimisation technique"],"prefix":"10.1049","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6836-6493","authenticated-orcid":false,"given":"Wathiq H.","family":"Dukhan","sequence":"first","affiliation":[{"name":"Faculty of Science Sana'a University  Sana'a Yemen"}]},{"given":"Marghny H.","family":"Mohamed","sequence":"additional","affiliation":[{"name":"Department of Computer Science Faculty of Computer and Information Assiut University  Assiut Egypt"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2002-948X","authenticated-orcid":false,"given":"Ali A.","family":"Amer","sequence":"additional","affiliation":[{"name":"Faculty of Applied Science Computer Science Department Taiz University  Taiz Yemen"}]},{"given":"Elnomery Allam","family":"Zanaty","sequence":"additional","affiliation":[{"name":"Department of Computer Science Faculty of Computers and Artificial Intelligence Sohag University  Sohag Egypt"}]},{"given":"Omar","family":"Reyad","sequence":"additional","affiliation":[{"name":"Faculty of Science Sohag University  Sohag 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