Design of efficient job shop scheduling rules
Proceedings of the 21st international conference on Computers and industrial engineering
Design of experiments: robust design: seeking the best of all possible worlds
Proceedings of the 32nd conference on Winter simulation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Computers and Industrial Engineering
A web-based simulation optimization system for industrial scheduling
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A simulation-based scheduling system for real-time optimization and decision making support
Robotics and Computer-Integrated Manufacturing
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
Simulation modeling has the capability to represent complex real-world systems in details and therefore it is suitable to develop simulation models for generating detailed operation plans to control the shop floor. In the literature, there are two major approaches for tackling the simulation-based scheduling problems, namely dispatching rules and using meta-heuristic search algorithms. The purpose of this paper is to illustrate that there are advantages when these two approaches are combined. More precisely, this paper introduces a novel hybrid genetic representation as a combination of both a partially completed schedule (direct) and the optimal dispatching rules (indirect), for setting the schedules for some critical stages (e.g. bottlenecks) and other non-critical stages respectively. When applied to an industrial case study, this hybrid method has been found to outperform the two common approaches, in terms of finding reasonably good solutions within a shorter time period for most of the complex scheduling scenarios.