Title: Scheduling comparison between multi-objective mathematical models and genetic algorithms approach in the textile industry

Authors: Can Celikbilek; Tugba Tunacan; Gürsel A. Süer; Omer Dulkadir

Addresses: Industrial and Systems Engineering Department, Russ College of Engineering and Technology, Ohio University, Athens, OH, 45701, USA ' Industrial Engineering Department, Karabuk University, Baliklarkayasi Mevkii 78050 Karabük, Turkey ' Industrial and Systems Engineering Department, Russ College of Engineering and Technology, Ohio University, Athens, OH, 45701, USA ' Safranbolu Vocational School, Karabuk University, Turkey

Abstract: This paper discusses mixed integer mathematical models and genetic algorithms (GAs) approach for finding an optimal schedule of the bottleneck machine for a company in the textile industry. Single-objective and multi-objective mathematical models and GA are used to obtain an optimal solution to minimise the maximum tardiness (Tmax). The comparison is made between mathematical models and GA according to the primary and secondary performance measures. Primary performance measure is Tmax, while secondary performance measure is number of tardy jobs (nt) and total tardiness (TT) values. The experimentation is performed for small and large size problems. All jobs have five different instances except for 150-job and 200-job problems. Due to memory and time limitations, only one sample could be solved for 150-job and 200-job problem. The experimental results indicated that, most of the time GA finds an optimal solution and proposes alternative schedules for both single-objective and multi-objective mathematical models.

Keywords: single objective models; multi-objective models; genetic algorithms; textile industry; textiles; scheduling; mixed integer programming; MIP; mathematical modelling; bottleneck machines; performance measures.

DOI: 10.1504/IJSOM.2016.078894

International Journal of Services and Operations Management, 2016 Vol.25 No.2, pp.236 - 258

Received: 19 Jan 2015
Accepted: 01 Mar 2015

Published online: 04 Sep 2016 *

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