Title: New dispatching rules and due date assignment models for dynamic job shop scheduling problems

Authors: Aydin Teymourifar; Gurkan Ozturk

Addresses: Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey; Computational Intelligence and Optimization Laboratory (CIOL), Anadolu University, 26555, Eskisehir, Turkey ' Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey; Computational Intelligence and Optimization Laboratory (CIOL), Anadolu University, 26555, Eskisehir, Turkey

Abstract: In this paper, new due date assignment models and dispatching rules have been designed for the dynamic job shop scheduling problem. All of them have competitive results compared to the models from previous studies. The proposed dispatching rules have been evolved based on the modified and composite features of jobs. They have been compared with successful methods from the literature in a simulated environment. The simulation model has been validated by comparing the results with an analytical method. One of the rules has the best results in comparison with the other dispatching rules from the literature cited in this study. Another important matter which is considered in this paper is that the due date assignment model must be compatible with the used dispatching rule. Based on this approach, new due date assignment models are developed, which have the best results when combined with some dispatching rules. [Submitted 17 August 2016; Accepted 14 November 2017]

Keywords: dynamic job shop scheduling; dispatching rules; due date assignment models; regression; neural networks; simulation.

DOI: 10.1504/IJMR.2018.095358

International Journal of Manufacturing Research, 2018 Vol.13 No.4, pp.302 - 329

Available online: 07 Sep 2018 *

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