Abstract

Knapsack problem is a classical combinatorial optimization problem; which hunt a best solution among various available solutions. In this paper a new hybrid GA-GSA algorithm is develop using genetic algorithm (GA) and gravitational search algorithm (GSA) for multidimensional knapsack problem (MDKP). In hybrid algorithm GA is used for global search and GSA is used for local search. Central interest of current work is to improve the quality of solution for MDKP in comparison of GA and GSA. In hybrid GA-GSA algorithm k%population is selected after creation of individuals by GA algorithm and rest (100-k) %population is selected after creation of individuals by GSA algorithm. In new approach top k% population is chosen as surviving population for ne w generation of GA. Hybrid GA-GSA performance has examine against GA and PSO for 10 standard MDKPs. Simulation outcomes show hybrid GA-GSA produce high quality solution in comparison of both approaches. However computational time is sacrified in case of hybrid GA-GSA for MDKP.

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