Title: Modified improved genetic algorithm to minimise tri-objective functions in a textile mill

Authors: S. Jeyakkannan; T. Prabaharan

Addresses: Department of Mechanical Engineering, Park College of Engineering and Technology, Coimbatore-641 659, Tamil Nadu, India ' Department of Mechanical Engineering, Mepco Schlenk College of Engineering, Sivakasi-626005, Tamil Nadu, India

Abstract: Efficient scheduling has become essential for manufacturing industries to survive in today's competitive business environment. A flow shop scheduling problem with processing times in textile yarn manufacturing mill is considered in this paper. The objective is to minimise the tri objective function of makespan time, meanflow time and machine idle time by using the exact sequencing method. To solve this problem modified improved genetic algorithm (MIGA) is proposed in this paper wherein multiple cross over operators and multiple mutation operators are fine tuned to obtain the above performance measures and the results show that the proposed algorithm can provide better results in textile industry problems when comparing with the results obtained through genetic algorithm (GA) and improved genetic algorithm (IGA).

Keywords: flowshop scheduling; make span; mean flow time; machine idle time; tri objective function; modified improved genetic algorithm; MIGA.

DOI: 10.1504/IJISE.2018.091433

International Journal of Industrial and Systems Engineering, 2018 Vol.29 No.1, pp.48 - 61

Received: 23 Dec 2015
Accepted: 30 Apr 2016
Published online: 01 May 2018 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article