Article ID: | iaor20162191 |
Volume: | 10 |
Issue: | 2 |
Start Page Number: | 80 |
End Page Number: | 88 |
Publication Date: | May 2016 |
Journal: | Journal of Simulation |
Authors: | Zhang T, Rose O |
Keywords: | manufacturing industries, combinatorial optimization, simulation, heuristics: genetic algorithms |
A special flexible job shop scheduling problem is presented. The problem has continuous‐operation constraints at the last stages. A formulation of the problem is given and an integrated approach combining the simulation of production processes and the genetic algorithm is used to solve the problem. The processing paths of all jobs are decision variables and designed to be one individual in the genetic algorithm. The simulation with the reverse process flows evaluates the feasibility and fitness values of individuals. A satisfactory solution can be obtained after evolution. In order to improve the robustness, certain amounts of jobs are always kept in front of the machines at the last stages. Finally, the proposed approach is applied to one steel‐making plant and compared with a hierarchical approach.