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We test our algorithm on portfolio optimization problems formed with the stocks included in the S&amp;P 100 index using expected return, liquidity, conditional value at risk, and mean absolute deviation as criteria. We simulate DM responses with linear and nonlinear preference functions and use various weights for the criteria. The experiments show that our algorithm is able to find highly-preferred solutions in considerably low number of iterations. We also test our algorithm against benchmark algorithms and demonstrate that our algorithm produces superior or comparable results. <\/jats:p>","DOI":"10.1142\/s0219622020500510","type":"journal-article","created":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T16:57:02Z","timestamp":1607619422000},"page":"371-398","source":"Crossref","is-referenced-by-count":6,"title":["A New Interactive Algorithm for Continuous Multiple Criteria Problems: A Portfolio Optimization Example"],"prefix":"10.1142","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9061-103X","authenticated-orcid":false,"given":"G\u00fcl\u015fah","family":"Karakaya","sequence":"first","affiliation":[{"name":"Department of Business Administration, Middle East Technical University, Ankara 06800, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ceren Tuncer","family":"\u015eakar","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Hacettepe University, Ankara 06800, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,1,18]]},"reference":[{"key":"S0219622020500510BIB001","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-3094-4_2"},{"key":"S0219622020500510BIB002","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5563-6"},{"key":"S0219622020500510BIB003","unstructured":"V. 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