Linkage based deferred acceptance optimization

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.