Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1057/jos.2015.20 | J. Simulation |
Keywords | Field | DocType |
scheduling, flexible job shop, simulation, genetic algorithm | Decision variables,Job shop scheduling,Computer science,Scheduling (computing),Simulation,Job shop,Flow shop scheduling,Robustness (computer science),Genetic algorithm,Discrete event simulation | Journal |
Volume | Issue | ISSN |
10 | 2 | 1747-7786 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Zhang | 1 | 33 | 11.25 |
| Oliver Rose | 2 | 17 | 10.43 |