Quantum-inspired ant colony optimisation algorithm for a two-stage permutation flow shop with batch processing machines

Chen, Zhen; 鄭, 旭光; Zhou, Shengchao; Liu, Chuang

doi:10.1080/00207543.2019.1661535

Cited by 12 publications

(4 citation statements)

References 47 publications

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“…With one machine at Stage 2, based on a branch and bound technique, [15] developed an algorithm to find an optimal schedule. With arbitrary arrival time of jobs, [16] present an ant colony algorithm to schedule a TSFS system. A multi-objective hybrid ant colony algorithm is constructed by [17] to trade off the makespan and total energy costs for a two-stage blocking permutation flow-shop.…”

Section: Literature Reviewmentioning

confidence: 99%

A Two-Step Approach to Scheduling a Class of Two-Stage Flow Shops in Automotive Glass Manufacturing

Qiao

et al. 2023

Machines

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Driven from real-life applications, this work aims to cope with the scheduling problem of automotive glass manufacturing systems, that is characterized as a two-stage flow-shop with small batches, inevitable setup time for different product changeover at the first stage, and un-interruption requirement at the second stage. To the best knowledge of the authors, there is no report on this topic from other research groups. Our previous study presents a method to assign all batches to each machine at the first stage only without sequencing the assigned batches, resulting in an incomplete schedule. To cope with this problem, if a mathematical programming method is directly applied to minimize the makespan of the production process, binary variables should be introduced to describe the processing sequence of all the products, not only the batches, resulting in huge number of binary variables for the model. Thus, it is necessary and challenging to search for a method to solve the problem efficiently. Due to the mandatory requirement that the second stage should keep working continuously without interruption, solution feasibility is essential. Therefore, the key to solve the addressed problem is how to guarantee the solution feasibility. To do so, we present a method to determine the minimal size of each batch such that the second stage can continuously work without interruption if the sizes of all batches are same. Then, the conditions under which a feasible schedule exists are derived. Based on the conditions, we are able to develop a two-step solution method. At the first step, an integer linear program (ILP) is formulated for handling the batch allocation problem at the first stage. By the ILP, we need then to distinguish the batches only, greatly reducing the number of variables and constraints. Then, the batches assigned to each machine at the first stage are optimally sequenced at the second step by an algorithm with polynomial complexity. In this way, by the proposed method, the computational complexity is greatly reduced in comparison with the problem formulation without the established feasibility conditions. To validate the proposed approach, we carry out extensive experiments on a real case from an automotive glass manufacturer. We run ILP on CPLEX for testing. For large-size problems, we set 3600 s as the longest time for getting a solution and a gap of 1% for the lower bound of solutions. The results show that CPLEX can solve 96.83% cases. Moreover, we can obtain good solutions with the maximum gap of 4.9416% for the unsolved cases.

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Section: Literature Reviewmentioning

confidence: 99%

A Two-Step Approach to Scheduling a Class of Two-Stage Flow Shops in Automotive Glass Manufacturing

Qiao

et al. 2023

Machines

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“…Abdel-Basset et al [45] A hybrid whale optimization algorithm Benavides and Ritt [46] Heuristics They stated that their new heuristics are more successful than the NEH algorithm as initial solution algorithms. Chen et al [47] Quantum-inspired ACO Kizilay et al [48] Variable block insertion heuristic They used their new heuristic within well-known metaheuristics and stated that their new heuristic is well fitted with well-known metaheuristics. Fernandez-Viagas and Framinan [49] A best-of-breed IG algorithm It is reported as the best-sofar approximate method for the problem.…”

Section: Ts With Blocking Constrainmentioning

confidence: 99%

Genetic Algorithm Application for Permutation Flow Shop Scheduling Problems

Arık¹

2022

Gazi University Journal of Science

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“…A preliminary study of the specific industrial setup which motivated our research was done in Ackermann et al (2020+). For studies from different areas of application we refer, for instance, to Li et al (2015), Zhou et al (2016), Tan et al (2018), Chen et al (2019), Li et al (2019). The problems typically stem from various industries, e.g.…”

Section: Literaturementioning

confidence: 99%

Scheduling a proportionate flow shop of batching machines

Hertrich

Weiß

Ackermann

et al. 2020

J Sched

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In this paper we study a proportionate flow shop of batching machines with release dates and a fixed number $$m \ge 2$$ m ≥ 2 of machines. The scheduling problem has so far barely received any attention in the literature, but recently its importance has increased significantly, due to applications in the industrial scaling of modern bio-medicine production processes. We show that for any fixed number of machines, the makespan and the sum of completion times can be minimized in polynomial time. Furthermore, we show that the obtained algorithm can also be used to minimize the weighted total completion time, maximum lateness, total tardiness and (weighted) number of late jobs in polynomial time if all release dates are 0. Previously, polynomial time algorithms have only been known for two machines.

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Quantum-inspired ant colony optimisation algorithm for a two-stage permutation flow shop with batch processing machines

Cited by 12 publications

References 47 publications

A Two-Step Approach to Scheduling a Class of Two-Stage Flow Shops in Automotive Glass Manufacturing

A Two-Step Approach to Scheduling a Class of Two-Stage Flow Shops in Automotive Glass Manufacturing

Genetic Algorithm Application for Permutation Flow Shop Scheduling Problems

Scheduling a proportionate flow shop of batching machines

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