Linkage based deferred acceptance optimization

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• 作者：Deep Kiran^a ; ^{dkiran5@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; B. K Panigrahi^a ; ^{bkpanigrahi@ee.iitd.ac.in" class="auth_mail" title="E-mail the corresponding author} ; Swagatam Das ; ^b ; ^{swagatamdas19@yahoo.co.in" class="auth_mail" title="E-mail the corresponding author} ; Nitesh Kumar^a ; ^{nitesh.shokeen@gmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Deferred acceptance algorithm ; Linkage strategy ; Evolutionary computation ; Global optimization
• 刊名：Information Sciences
• 出版年：2016
• 出版时间：1 July 2016
• 年：2016
• 卷：349-350
• 期：Complete
• 页码：65-76
• 全文大小：523 K

文摘

In general, heuristic optimization techniques lose some of the optimal solution of the objective function in the optimization process. This paper proposes a concept to retain those variables that might help in accelerating the complete optimization process. The motivation is to derive linkages between variables in a population set that will be used in crossover strategy. This crossover strategy is dependent on a deferred acceptance algorithm (DAA). Also, the property of linkages or interrelation is implemented to derive the relation between variables among dimensions. This paper proposes a linkage based deferred acceptance optimization (LDAO) technique. It is observed that the proposed algorithm has proved its efficacy on the set of unconstrained and constrained objective functions. Also, the proposed algorithm is tested on challenging real world problems (CEC 2011) and the functions present in CEC 2014 competition.