Abstract
The steel continuous casting planning and scheduling problem namely SCC is a particular hybrid (flexible) flowshop that includes stages: (i) the converters (CV), (ii) the refining stands (RS) and (iii) the continuous casting (CC) stages. In this paper we study the SCC with inter-sequence dependent setups and dedicated machines at the last stage. The batch sequences are assumed to be pre-determined for one of the CC devices with a non preemptive scheduling process. The aim is to schedule the batches for each CC machine including the times setup between two successive sequences. We model the problem as a MILP where the objective is to minimize the makespan Cmax that we formulate as the largest completion time taking account of the setup times for each CC. Then, we propose an adapted genetic algorithm that we call Regeneration GA (RGA) to solve the problem. We use a randomly generated instances of several sizes to test the model and for which we do not know an optimal solution. The method is able to solve the problems in an acceptable time for medium and large instances while a commercial solver was able to solve only small size instances.
Highlights
The steel continuous casting problem (SCC) is a particular scheduling problem that arises from the steel making industry
The production is organized with regards to a given number of operations or stages to be accomplished with respect to the same order
In the SCC problem ≡ Pm1,Qm2,RMm3 || σ | Cmax, the production orders are represented by a set of the cast sequences where each sequence is dedicated to a continuous castings (CC) machine at the last stage
Summary
The steel continuous casting problem (SCC) is a particular scheduling problem that arises from the steel making industry. The classical flowshop problem (FSP) considers only one machine at each stage, while its generalization considers a set of devices in series with multicapacity in parallel, called a hybrid flowshop problem (HFS). To the notation by [7], we write the SCC problem as a 3-stages hybrid flowshop (HFS): (Pi)m i=11,(Qj)m j=21,(Rk)m k=31 || σ | Cmax, where || stands for a parallel system and σ is the inter-sequence setup time (Fig. 2). The m-stages HFS with unrelated parallel machines and dependent setup times has been proven to be NP-hard (see [14, 16]). We recall that the proposed problem has a very complex structure, where small size problems could be difficult to solve to their optimum in a reasonable run time To overcome this difficulty, we intend to develop an approximate approach to solve the SCC.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
