http://orcid.org/0000-0001-9813-1233
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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.
Acknowledgements
The author would like to thank the Editor and reviewers for their valuable comments and suggestions which helped to improve the paper. In addition, the authors would like to acknowledge the financial support of University of Tehran for this research under grant number 29922/1/01.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplemental data
The underlying research materials for this article can be accessed at http://dx.doi.org/10.1080/0951192X.2017.1307452.