{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T09:10:17Z","timestamp":1722244217989},"reference-count":8,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Found. Comput. Sci."],"published-print":{"date-parts":[[2005,4]]},"abstract":"<jats:p> This paper discusses the design of a parallel genetic algorithm to generate solutions to multi-objective problems. The algorithm uses multiple optimization criteria, independent cross-pollinating populations, and handles multiple hard constraints. Individuals in the population consist of multiple chromosomes. The complexity of the algorithm is the number of generations processed times O(N<jats:sup>2<\/jats:sup>) where N is the total number of individuals used for path generation on any of the optimizations. The results of initial empirical studies on the effects of pollination and recommendations for possible future work are presented. <\/jats:p>","DOI":"10.1142\/s012905410500298x","type":"journal-article","created":{"date-parts":[[2005,4,27]],"date-time":"2005-04-27T07:12:19Z","timestamp":1114585939000},"page":"261-280","source":"Crossref","is-referenced-by-count":6,"title":["CROSS-POLLINATING PARALLEL GENETIC ALGORITHMS FOR MULTI-OBJECTIVE SEARCH AND OPTIMIZATION"],"prefix":"10.1142","volume":"16","author":[{"given":"LUCAS A.","family":"WILSON","sequence":"first","affiliation":[{"name":"Computing and Mathematical Sciences, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, United States of America"}]},{"given":"MICHELLE D.","family":"MOORE","sequence":"additional","affiliation":[{"name":"Computing and Mathematical Sciences, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, United States of America"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574798000034"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1142\/1111"},{"key":"rf9","volume-title":"Genetic Algorithms Search, Optimization, and Machine Learning","author":"Goldberg D.","year":"1989"},{"key":"rf10","first-page":"332","volume":"6","author":"Goldberg D.","journal-title":"Complex Systems"},{"key":"rf11","volume-title":"Adaptation in Natural and Artificial Systems","author":"Holland J.","year":"1975"},{"key":"rf12","volume-title":"Automated Synthesis and Optimization of Robot Configurations: An Evolutionary Approach","author":"Leger P.","year":"1999"},{"key":"rf13","doi-asserted-by":"publisher","DOI":"10.1016\/j.parco.2003.12.005"},{"key":"rf14","unstructured":"J.\u00a0Periaux, M.\u00a0Sefrioui and B.\u00a0Mantel, Genetic Algorithms and Evolution Strategies in Engineering and Computer Science: Recent Advances and Industrial Applications, eds. D.\u00a0Quagliarella (John Wiley and Sons Ltd., Chichester, UK, 1995)\u00a0pp. 225\u2013243."}],"container-title":["International Journal of Foundations of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S012905410500298X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T11:27:07Z","timestamp":1565177227000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S012905410500298X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,4]]},"references-count":8,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2011,11,20]]},"published-print":{"date-parts":[[2005,4]]}},"alternative-id":["10.1142\/S012905410500298X"],"URL":"https:\/\/doi.org\/10.1142\/s012905410500298x","relation":{},"ISSN":["0129-0541","1793-6373"],"issn-type":[{"value":"0129-0541","type":"print"},{"value":"1793-6373","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,4]]}}}