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Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems. However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time. This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to...
The ant system is a metaheuristic developed for the solution of hard combinatorial optimization problems. Capacitated vehicle routing problem(CVRP) is an important combinatorial optimization problem which has received considerable attention in the last decades. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony Algorithm (ACA), a CVRP is examined and...
In this paper we present a study of an Ant Colony System (ACS) for the two-dimensional strip packing problem. In our computational study, we emphasize the influence of incorporating a simple optimization method at each cycle of the ACS. In this hybrid approach, local optimization is applied to a subset of the newly generated solutions to move them to a local optimum. We show that our ACS algorithm,...
The ant colony system (ACS) algorithm is vital in solving combinatorial optimization problems. However, the weaknesses of premature convergence and low efficiency greatly restrict its application. In order to improve the performance of the algorithm, the hybrid ant colony system (HACS) is presented by introducing the pheromone adjusting approach, combining ACS with saving and interchange methods,...
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