In this paper, the Gravitational Search Algorithm (GSA) is hybridized with real coded Genetic Algorithm to solve integer and mixed integer programming problems. The idea is based on two earlier papers of the authors. ...
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ISBN:
(数字)9789811033223
ISBN:
(纸本)9789811033223;9789811033216
In this paper, the Gravitational Search Algorithm (GSA) is hybridized with real coded Genetic Algorithm to solve integer and mixed integer programming problems. The idea is based on two earlier papers of the authors. In the first paper, the authors proposed a methodology in which the Laplace Crossover and Power Mutation were embedded in Gravitational Search Algorithm and in the second paper, these algorithms were extended for the case of constrained optimization problems. In order to deal with integer variables, a special method is adopted. For dealing with the constraints the Deb's technique is implemented. The original GSA and three new variants are tested on a set of benchmark problems available in literature. Based on the extensive numerical and graphical analysis of results it is concluded that one of the proposed variants outperform the original GSA and the other proposed variants.
In this paper, a computational algorithm, named RST2ANU algorithm, has been developed for solving integer and mixedinteger global optimization problems. This algorithm, which primarily is based on the original contro...
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In this paper, a computational algorithm, named RST2ANU algorithm, has been developed for solving integer and mixedinteger global optimization problems. This algorithm, which primarily is based on the original controlled random search approach of Price [22i], incorporates a simulated annealing type acceptance criterion in its working so that not only downhill moves but also occasional uphill moves can be accepted. In its working it employs a special truncation procedure which not only ensures that the integer restrictions imposed on the decision variables are satisfied, but also creates greater possibilities for the search leading to a global optimal solution. The reliability and efficiency of the proposed RST2ANU algorithm has been demonstrated on thirty integer and mixedinteger optimization problems taken from the literature. The performance of the algorithm has been compared with the performance of the corresponding purely controlled random search based algorithm as well as the standard simulated annealing algorithm. The performance of the method on mathematical models of three realistic problems has also been demonstrated.
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