Hybrid Algorithm Based on Ant and Genetic Algorithms for Task Allocation on a Network of Homogeneous Processors

Abstract

In the field of parallel computing, there is an essential problem which is called Task Allocation Problem(TAP). The task allocation problem (TAP) is a problem where many of tasks require to be allocated to a set of processors.The number of m tasks that is needed to be allocated with number of n processors where (m>n) so that the time needed to process all the tasks is minimized. This paper presents an efficient algorithm (TAP_ACO_GA) to solve the task allocation problem. The proposed algorithm is based on the idea of Ant Colony Optimization Algorithm(ACO) and the idea of Genetic Algorithm (GA) .The proposed algorithm is tested in different dataset and its results are compared with the results in[2]and the results show that TAP_ACO_GA is better than the other algorithm.

Web page ranking using ant colony optimisation and genetic algorithm for effective information retrieval

“…GA is used subsequently to apply crossover and mutation operations to generate a new population. In Shuqeir and Al Qublan (2014) hybrid algorithm based on ant and GA is proposed for task allocation on a network of homogeneous processors. In Zukhri and Paputungan (2013) GA-ACO is used for travelling salesman problem.…”