Abstract
Parallel machine scheduling, also known as parallel task scheduling, involves the assignment of multiple tasks onto the system architecture's processing components (a bank of machines in parallel). This paper presents a general purpose spreadsheet based genetic algorithm (GA) approach to minimize the makespan (total completion time) for a set of tasks for identical parallel machines and worker assignment to machines. The performance of the proposed approach is compared against two data sets of benchmark problems available on the internet. The proposed approach produces optimal solution for almost 95 percent of the problems demonstrating the effectiveness of the proposed approach.