{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T07:23:41Z","timestamp":1648884221802},"reference-count":19,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2008,12]]},"abstract":"<jats:p> A new crossover technique for genetic algorithms is proposed in this paper. The technique is called probabilistic adaptive crossover and denoted by PAX. The method includes the estimation of the probability distribution of the population, in order to store in a unique probability vector P information about the best and the worse solutions of the problem to be solved. The proposed methodology is compared with six crossover techniques namely: one-point crossover, two-point crossover, SANUX, discrete crossover, uniform crossover and selective crossover. These methodologies were simulated and compared over five test problems described by ONEMAX Function, Royal Road Function, Random L-MaxSAT, Bohachevsky Function, and the Himmelblau Function. <\/jats:p>","DOI":"10.1142\/s0218213008004333","type":"journal-article","created":{"date-parts":[[2009,1,7]],"date-time":"2009-01-07T10:43:05Z","timestamp":1231324985000},"page":"1131-1160","source":"Crossref","is-referenced-by-count":1,"title":["PROBABILISTIC ADAPTIVE CROSSOVER (PAX): A NOVEL GENETIC ALGORITHM CROSSOVER METHODOLOGY"],"prefix":"10.1142","volume":"17","author":[{"given":"SEBASTI\u00c1N A.","family":"SALAH","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, University of Chile, Av. Tupper 2007, Casilla 412-3, Santiago, Chile"}]},{"given":"MANUEL A.","family":"DUARTE-MERMOUD","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, University of Chile, Av. Tupper 2007, Casilla 412-3, Santiago, Chile"}]},{"given":"NICOL\u00c1S H.","family":"BELTR\u00c1N","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, University of Chile, Av. Tupper 2007, Casilla 412-3, Santiago, Chile"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/1090.001.0001","volume-title":"Adaptation in Natural and Artificial Systems","author":"Holland J. H.","year":"1992"},{"key":"rf2","volume-title":"Numerical Optimization of Computer Models","author":"Schwefel H. 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