A simulation optimisation approach for real-time scheduling in an open shop environment using a composite dispatching rule. Issue 12 (2nd December 2017)

• Record Type: Journal Article
• Authors: Nasiri, Mohammad Mahdi; Yazdanparast, Reza; Jolai, Fariborz
• Is Part Of: International journal of computer integrated manufacturing. Volume 30:Issue 12(2017)
• Page Start: 1239
• Page End: 1252
• Publication Date: 2017-12-02
• Subjects: simulation applications -- open shop scheduling -- dispatching rule -- neural network applications -- data envelopment analysis; Computer integrated manufacturing systems -- Periodicals; 670.427
• DOI: 10.1080/0951192X.2017.1307452
• Languages: English
• ISSNs: 0951-192X

Abstract

Abstract : In the last decades, many researchers have studied open shop scheduling (OSS) problem by considering deterministic parameters using mathematical modelling, heuristics and meta-heuristics. However, it is important to study the problem as close as possible to real world conditions which consists of uncertainty and stochastic parameters. In this study, dispatching rules, as accepted tools for real-time scheduling, are applied for optimising the OSS problem. Since none of conventional dispatching rules performs well for all performance measures, a simulation-based real-time scheduling composite dispatching rule is developed. For this purpose, a multi response optimisation approach based on computer simulation for scheduling a non-preemptive open shop with stochastic ready times is presented in order to minimise the mean waiting time of jobs. The presented approach composed of design of experiments, discrete event simulation, multi-layer perceptron artificial neural network, radial basis function and data envelopment analysis to determine the most efficient dispatching rule for each machine.