An Efficient Augmented Lagrange Multiplier Method for Steelmaking and Continuous Casting Production Scheduling
| Autor: | Dan Li, Liuyang Yuan, Nikolaos Rakovitis, Dayong Han, Jie Li, Qiuhua Tang, Zikai Zhang |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Schedule 021103 operations research Linear programming Job shop scheduling Computer science General Chemical Engineering 0211 other engineering and technologies 02 engineering and technology General Chemistry Solver symbols.namesake 020901 industrial engineering & automation Lagrangian relaxation Lagrange multiplier symbols Relaxation (approximation) Subgradient method |
| Zdroj: | Chemical Engineering Research and Design. 168:169-192 |
| ISSN: | 0263-8762 |
| Popis: | The steelmaking and continuous casting (SCC) process is one of the vital processes in iron and steel plants since it determines chemical compositions of slabs and is often a bottleneck for iron and steel manufacturing. In this paper, we first develop a discrete-time mixed-integer linear programming (MILP) formulation for a new SCC scheduling problem where different processing routes are used to produce diversified and personalized slab products. To solve the proposed MILP formulation efficiently, we then propose a novel efficient solution algorithm using Augmented Lagrange multiplier method (e-ALM) through relaxation of the coupling constraints and incorporation of penalty components. A heuristic-based list scheduling approach as well as adjacent pairwise swap operations is used to construct a high-quality feasible schedule. A fine-adjusting strategy based on the subgradient direction is proposed to update Lagrangian multipliers dynamically to speed up the convergence. It is shown that the proposed e-ALM is able to generate optimal or near-optimal solutions with 5% optimality for 150 industrial-scale instances and outperform the commercial solver GAMS/CPLEX and the existing Lagrangian relaxation algorithms with better feasible solutions and smaller duality gap within the specified computational time. |
| Databáze: | OpenAIRE |
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