Application of Genetic Algorithm in Flowshop to Minimize Makespan

Abstract— In this article presents an approach based on the application of Genetic Algorithm with the help of Exponential distribution factor (EPDT), to solve the problem of scheduling a permutation flow shop of n jobs on m machines when all jobs are available for processing. The objective is to minimize the makespan. Many researches planned various algorithms to achieve these objectives through an optimal sequence in a PFS. For identifying an optimal sequence for ‘n’ jobs in ‘m’ machines, sequences are to be worked. This planned heuristic approach, approximately solve the problem that consists in scheduling the jobs using Exponential Distribution factor which helps in developing a mathematical model with less computational instance. For the evaluation we use Ruben Ruiz well know standard problem using MAT LAB. The result shows that the planned algorithm is very effective and at the same time is easy to implement. Finally the results of newly planned heuristic are better when compare to the makespan of other heuristics; Palmer, Gupta, CDS and RA.