| Title |
Sequencing jobs with asymmetric costs and transition constraints in a finishing line: A real case study |
| ID_Doc |
15990 |
| Authors |
Alvarez-Gil, N; García, SA; Rosillo, R; de la Fuente, D |
| Title |
Sequencing jobs with asymmetric costs and transition constraints in a finishing line: A real case study |
| Year |
2022 |
| Published |
|
| DOI |
10.1016/j.cie.2021.107908 |
| Abstract |
Production scheduling plays a vital role in industrial manufacturing due to the potential impact on the production costs and service levels of a company. It consists in finding the best sequence in which some items should be produced, optimizing one or multiple performance indicators, such as the production cost or total time span. In this work we study the real-world problem of sequencing steel coils in a continuous galvanizing line and the challenges it poses. The production of new steel grades and the growing necessity or reducing the stock levels at the galvanizing line have brought an important increase in the number of sequencing constraints, challenging feasibility and the algorithms in use. We explain some issues of the current Ant Colony Optimization algorithms and introduce a new hybrid version, the Ant System with Interval Reconstruction (AS-IR), that notably enhances the feasibility performance. The new hybrid algorithm uses the Interval Reconstruction (IR), a novel constructive local search algorithm initially developed to solve constraint violations, and then extended to also help reduce the sequencing costs. All the key features of the IR and how it is used in the hybrid algorithm are explained in detail. The experiments conducted with 30 real instances show how the proposed AS-IR hybrid algorithm achieves much better results, guaranteeing feasible sequences when the set of coils is sequenceable, as well as finding lower-cost solutions. |
| Author Keywords |
Combinational optimization; Steel industry; Sequencing; Metaheuristics |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000746998000004 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Industrial |
| Research Area |
Computer Science; Engineering |
| PDF |
https://doi.org/10.1016/j.cie.2021.107908
|