Title
A Robust Optimization Approach For Integrated Steel Production And Batch Delivery Scheduling With Uncertain Rolling Times And Deterioration Effect
Abstract
Efficient collaboration between various sub-processes of steel production is of considerable significance, which directly affects a product's production cycle and energy consumption. However, current collaborative optimisation models and methods in steel production are still limited: (1) Most of the current collaborative manufacturing problems in steel production focus on obtaining joint schedule between steel-making and continuous casting (SCC), and the works considering continuous casting and hot rolling (CCHR) are very few. (2) The processing time is assumed as a constant in most of the existing SCC scheduling models. However, the rolling time of a product in hot rolling operation is actually uncertain and deteriorating. (3) Exact algorithms cannot be applied to solve the complicated collaborative optimisation problems because of their high complexities. To address these problems, we propose an integrated CCHR and batch delivery scheduling model where interval rolling time and linear deterioration effect are considered. With the concept of min-max regret value, we formulate the collaborative optimisation problem as a robust optimisation problem. Instead of using the exact algorithm, we develop an Improved Variable Neighborhood Search (IVNS) algorithm incorporated a novel population update mechanism and neighbourhood structures to solve the robust optimisation problem. Moreover, we develop an exact algorithm that combines CPLEX solver and two dynamic programming algorithms to obtain the maximum regret value of a given rolling sequence. The results of computational experiments show the excellent performance of the proposed algorithms.
Year
DOI
Venue
2020
10.1080/00207543.2019.1693659
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Keywords
DocType
Volume
production and delivery, uncertain rolling times, deteriorating jobs, batch delivery, IVNS
Journal
58
Issue
ISSN
Citations 
17
0020-7543
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Min Kong1193.65
Jun Pei220226.56
Jin Xu300.34
Xin-Bao Liu425426.14
Xiaoyu Yu500.34
P. M. Pardalos626945.19