Task Scheduling using Parallel Genetic Simulated Annealing Algorithm

Abstract

Task scheduling is a NP-hard problem and is an integral part of parallel and distributed computing. This paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing algorithm and applied to solve task scheduling in grid computing. It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively. When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.