A heuristic genetic algorithm for Bi-Criteria flow shop scheduling with fuzzy processing time and due time Kumar Harendra1, Kumar Pankaj1,*, Sharma Manisha2 1Department of Mathematics and Statistics, Gurukula Kangri University, Hardwar, 249404, Uttarakhand, India 2Department of Mathematics, Panjab University, Chandigarh, 160014, Punjab, India *Corresponding Author: Pankaj Kumar, Department of Mathematics and Statistics, Gurukula Kangri University, Hardwar, 249404, Uttarakhand, India, E-mail: pmittalvce@gmail.com
Online published on 16 January, 2018. Abstract The bi-criteria flow shop scheduling problem is widely studied optimization problem in which every machine has same work function and a job can be processed by any of available machines. The present research work includes a new genetic algorithm for solving the bi-criteria flow shop scheduling problem. The proposed genetic algorithm has own coding, evaluation function, crossover and mutation to minimize the maximum tardiness and weighted flow time. In this paper, cycle crossover operators for crossover and interchanging mutation operators for mutation are used. The objective of this paper is to find an optimal scheduling of ‘n ’jobs for 3 machines involving processing times, due time and weightage of jobs. The processing times of jobs have been considered as a fuzzy number to denote uncertainty of processing time which is more realistic and general in nature. The fuzzy processing times are defuzzified and converted into crisp one using fuzzy number ranking method. The present algorithm is collated with beforehand released problems in literature. The proposed algorithm is formulated and applied to numerical examples to demonstrate its effectiveness. Top Keywords Scheduling, genetic algorithm, fuzzy processing time, maximum tardiness, weighted flow time, due time. Top |