A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

Jiang, Sheng-Long; Liu, Min; Hao, Jinghua; Qian, Wangping

doi:10.1016/j.cie.2015.06.002

Cited by 62 publications

(12 citation statements)

References 33 publications

(39 reference statements)

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“…Some studies already consider the casting time in the machine not only as a decision variable that allows to optimize the process. 26) In case of having an algorithm that provides the ideal schedule, it is not only necessary that it adapts to the different levels of severity of unforeseen events, but also that it knows how to discern the ideal solutions at the time of the event. 66) Any change in the temperature route during the whole process can be taken into account as a contingence, as long as it can be needed more time to accomplished some stage.…”

Section: Contingenciesmentioning

confidence: 99%

Scheduling in Continuous Steelmaking Casting: A Systematic Review

et al. 2020

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The converter furnace and the continuous casting are the most important stages in steel production. Modern integrated processes directly connect the converter furnaces and the continuous casting machines with a flow of molten metal, and the steel is manufactured synchronously between the various machines. Starting from the traditional handmade programs for the management of these processes, during the last two decades there has been a notable increase in studies and publications in this field, trying to formulate scheduling in a rational and automatic way. The process has been approached for years through the development of both physical and operational research models, many of them theoretically. The main purpose of this study is to present a critical and in-depth evaluation of the previous studies, so that the state of the art of scheduling in steelworks can be evaluated. An approach based on a Systematic Literature Review (SLR) has been used, trying to search, evaluate, synthesize and analyze all the relevant studies for this specific field. As a result, the conclusions of the various analyses are presented and a study route is proposed for the design of the optimal planning methodology in the steelworks.

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Section: Contingenciesmentioning

confidence: 99%

Scheduling in Continuous Steelmaking Casting: A Systematic Review

et al. 2020

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“…To ensure that the rolled coil quality remains acceptable, we should replace working rollers after rolling a certain number of slabs. In the real world, a scheduling problem in the steel industry is a complex problem; therefore, a wide variety of approaches have been applied to solve it: a hybrid differential evolution algorithm is proposed by Jiang et al 21 Pan and Yang formulated this problem as a multiple route problem with multiple objectives. The procedure for solving this problem is based on a partial set-partitioning formulation; 22 a heuristic rescheduling algorithm is proposed that has the minimum total waiting time, 23 and a two-stage scheduling method is proposed for solving the hot rolling scheduling problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a scheduling decision support system for the skin pass line: A case study of the steel finishing line

Vaez

Jabbarzadeh

Azad

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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In this paper, we investigate the scheduling policies in the iron and steel industry, and in particular, we formulate and propose a solution to a complicated problem called skin pass production scheduling in this industry. The solution is to generate multiple production turns for the skin pass coils and, at the same time, determine the sequence of these turns so that productivity and product quality are maximized, while the total production scheduling cost, including the costs of tardiness, flow of material, and the changeover cost between adjacent and non-adjacent coils, is minimized. This study has been prompted by a practical problem in an international steel company in Iran. In this study, we present a new mixed integer programming model and develop a heuristic algorithm, as the commercial solvers would have difficulty in solving the problem. In our heuristic algorithm, initial solutions are obtained by a greedy constraint satisfaction algorithm, and then a local search method is developed to improve the initial solution. The experimental results tested on the data collected from the steel company show the efficiency of the proposed heuristic algorithm by solving a large-sized instance in a reasonable computation time. The average deviation between the manual method and the heuristic algorithm is 30%. Also, in all the components of the objective function, the algorithm performs better compared to the manual method. The improved values are greater than 15. In addition, we develop a commercial decision support system for the implementation of the proposed algorithm in the steel company.

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“…Thus, welding scheduling problem (WSP) plays an important role in promoting an enterprise to be a manufacturing giant. However, studies on the WSP are relatively scarce in comparison with other real-world scheduling problems such as steelmaking scheduling issues [2][3][4][5][6][7][8][9] . The main reasons for few researches on the real-world WSP may be the following aspects.…”

Section: Introductionmentioning

confidence: 99%

An effective multi-objective discrete grey wolf optimizer for a real-world scheduling problem in welding production

Xiao

et al. 2016

Advances in Engineering Software

108

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a b s t r a c tThis paper aims to provide a solution method for a real-world scheduling case from a welding process, which is one of the important processes in modern industry. The unique characteristic of the welding scheduling problem (WSP) is that multiple machines can process one operation at a time. Thus, WSP is a new scheduling problem. We first formulate a new multi-objective mixed integer programming model for this WSP based on a comprehensive investigation. This model involves some realistic constraints, controllable processing times (CPT), sequence dependent setup times (SDST) and job dependent transportation times (JDTT). Then we propose a multi-objective discrete grey wolf optimizer (MODGWO) considering not only production efficiency but also machine load on this real-world scheduling case. The solution is encoded as a two-part representation including a permutation vector and a machine assignment matrix. A reduction machine load strategy is used to adjust the number of machines aiming to minimize the machine load. To evaluate the effectiveness of the proposed MODGWO, we compare it with other well-known multi-objective evolutionary algorithms including NSGA-II and SPEA2 on a set of instances. Experimental results demonstrate that the proposed MODGWO is superior to the compared algorithms in terms of convergence, spread and coverage on most instances. Finally, MODGWO is successfully applied to this real-world WSP. This implies that the proposed model is feasible and the proposed algorithm can solve this real-world scheduling problem very well.

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A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

Cited by 62 publications

References 33 publications

Scheduling in Continuous Steelmaking Casting: A Systematic Review

Scheduling in Continuous Steelmaking Casting: A Systematic Review

Designing a scheduling decision support system for the skin pass line: A case study of the steel finishing line

An effective multi-objective discrete grey wolf optimizer for a real-world scheduling problem in welding production

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