208 Task Graph Scheduling on Multiprocessor by Using New Genetic Algorithm

Multiprocessor task scheduling is an important and computationally difficult problem so has known an NP-Hard problem. Due to the NP-hard nature of the task scheduling problem, there are based on heuristics that try to produce good rather than optimal schedules. A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. We design a new encoding mechanism with functional chromosome that uses the priority representation based on random for run tasks in Diagram Acyclic Graph (DAG). It can represent a task schedule efficiently and assign tasks to processors. The proposed priority based GA has show effective performance in various parallel environments for scheduling methods.