MULTIPROCESSOR SCHEDULING BASED ON GENETIC ALGORITHMS

This paper presents the development of genetic algorithm approach to schedule tasks on a multiprocessor system. The objective is to minimize the make-span i.e. the completion time of all tasks while maintaining the precedence constraints within the task graph. No inter-processor communication overheads are assumed. The array data structure is employed for string representation and a hybrid selection method for reproduction is adopted. The ability of the genetic-based scheduler to deal with resource failures and apperiodic operations is also explored