{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T03:20:35Z","timestamp":1782876035262,"version":"3.54.5"},"reference-count":10,"publisher":"MIT Press - Journals","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Evolutionary Computation"],"published-print":{"date-parts":[[2005,12]]},"abstract":"<jats:p> Since the suggestion of a computing procedure of multiple Pareto-optimal solutions in multi-objective optimization problems in the early Nineties, researchers have been on the look out for a procedure which is computationally fast and simultaneously capable of finding a well-converged and well-distributed set of solutions. Most multi-objective evolutionary algorithms (MOEAs) developed in the past decade are either good for achieving a well-distributed solutions at the expense of a large computational effort or computationally fast at the expense of achieving a not-so-good distribution of solutions. For example, although the Strength Pareto Evolutionary Algorithm or SPEA (Zitzler and Thiele, 1999) produces a much better distribution compared to the elitist non-dominated sorting GA or NSGA-II (Deb et al., 2002a), the computational time needed to run SPEA is much greater. In this paper, we evaluate a recently-proposed steady-state MOEA (Deb et al., 2003) which was developed based on the \u03b5-dominance concept introduced earlier (Laumanns et al., 2002) and using efficient parent and archive update strategies for achieving a well-distributed and well-converged set of solutions quickly. Based on an extensive comparative study with four other state-of-the-art MOEAs on a number of two, three, and four objective test problems, it is observed that the steady-state MOEA is a good compromise in terms of convergence near to the Pareto-optimal front, diversity of solutions, and computational time. Moreover, the \u03b5-MOEA is a step closer towards making MOEAs pragmatic, particularly allowing a decision-maker to control the achievable accuracy in the obtained Pareto-optimal solutions. <\/jats:p>","DOI":"10.1162\/106365605774666895","type":"journal-article","created":{"date-parts":[[2005,11,5]],"date-time":"2005-11-05T22:58:46Z","timestamp":1131231526000},"page":"501-525","source":"Crossref","is-referenced-by-count":579,"title":["Evaluating the \u03b5-Domination Based Multi-Objective Evolutionary Algorithm for a Quick Computation of Pareto-Optimal Solutions"],"prefix":"10.1162","volume":"13","author":[{"given":"Kalyanmoy","family":"Deb","sequence":"first","affiliation":[{"name":"Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology Kanpur, Kanpur, PIN 208016, INDIA,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manikanth","family":"Mohan","sequence":"additional","affiliation":[{"name":"Manikanth Mohan, Palappallil House, Nalkalickal P.O., (via) Aranmula, Pathnamthitta (Dist), Kerala, PIN 689533, INDIA,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shikhar","family":"Mishra","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Missouri, St. Louis, MO 63121, USA,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","reference":[{"key":"p_2","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1999.7.3.205"},{"issue":"2","key":"p_4","first-page":"115","volume":"9","author":"Deb K.","year":"1995","journal-title":"Complex Systems"},{"key":"p_5","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"issue":"4","key":"p_6","first-page":"30","volume":"26","author":"Deb K.","year":"1996","journal-title":"Computer Science and Informatics"},{"key":"p_15","doi-asserted-by":"publisher","DOI":"10.1162\/106365600568167"},{"key":"p_16","doi-asserted-by":"publisher","DOI":"10.1162\/106365602760234108"},{"key":"p_18","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1994.2.3.221"},{"key":"p_19","doi-asserted-by":"publisher","DOI":"10.1162\/106365600568202"},{"key":"p_22","doi-asserted-by":"publisher","DOI":"10.1109\/4235.797969"},{"key":"p_23","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2003.810758"}],"container-title":["Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/106365605774666895","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:31:07Z","timestamp":1615584667000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/evco\/article\/13\/4\/501-525\/1219"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,12]]},"references-count":10,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2005,12]]}},"alternative-id":["10.1162\/106365605774666895"],"URL":"https:\/\/doi.org\/10.1162\/106365605774666895","relation":{},"ISSN":["1063-6560","1530-9304"],"issn-type":[{"value":"1063-6560","type":"print"},{"value":"1530-9304","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,12]]}}}