Minimising maximum tardiness in assembly flowshops with setup times

Aydilek, Asiye; Aydilek, Harun; Allahverdi, Ali

doi:10.1080/00207543.2017.1387300

Cited by 13 publications

(4 citation statements)

References 28 publications

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“…(2) Sequence-independent setup time is only related to the current processing operation. Aydilek et al (2017) proposed a new hybrid simulated annealing insertion algorithm in the context of two-stage assembly shop by considering the sequence-independent setup time. It had been verified that the proposed algorithm shares similar performance with the algorithm of self-adaptive differential evolution which has the best performance for such a problem.…”

Section: Literature Reviewmentioning

confidence: 99%

An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading

Peng

Xiao

et al. 2020

J Intell Manuf

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Many manufacturing systems need more than one type of resource to co-work with. Commonly studied flexible job shop scheduling problems merely consider the main resource such as machines and ignore the impact of other types of resource. As a result, scheduling solutions may not put into practice. This paper therefore studies the dual resource constrained flexible job shop scheduling problem when loading and unloading time (DRFJSP-LU) of the fixtures is considered. It formulates a multi-objective mathematical model to jointly minimize the makespan and the total setup time. Considering the influence of resource requirement similarity among different operations, we propose a similarity-based scheduling algorithm for setup-time reduction (SSA4STR) and then an improved non-dominated sorting genetic algorithm II (NSGA-II) to optimize the DRFJSP-LU. Experimental results show that the SSA4STR can effectively reduce the loading and unloading time of fixtures while ensuring a level of makespan. The experiments also verify that the scheduling solution with multiple resources has a greater guiding effect on production than the scheduling result with a single resource.

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Section: Literature Reviewmentioning

confidence: 99%

An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading

Peng

Xiao

et al. 2020

J Intell Manuf

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“…Aydilek et al [41] addressed a scheduling problem to minimize order delays, in which the setup times were independent of the processing times, through the application of algorithms of self-adaptive differential evolution and hybrid and simulated insertion algorithms. A scheduling problem with different approaches to setup times, aiming to minimize the makespan with the application of an enhanced version of the ACO algorithm, was studied in [24,25].…”

Section: Review About Scheduling Sequence-dependent Setups In Unrelat...mentioning

confidence: 99%

A Statistical Comparison of Metaheuristics for Unrelated Parallel Machine Scheduling Problems with Setup Times

et al. 2022

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Manufacturing scheduling aims to optimize one or more performance measures by allocating a set of resources to a set of jobs or tasks over a given period of time. It is an area that considers a very important decision-making process for manufacturing and production systems. In this paper, the unrelated parallel machine scheduling problem with machine-dependent and job-sequence-dependent setup times is addressed. This problem involves the scheduling of tasks on unrelated machines with setup times in order to minimize the makespan. The genetic algorithm is used to solve small and large instances of this problem when processing and setup times are balanced (Balanced problems), when processing times are dominant (Dominant P problems), and when setup times are dominant (Dominant S problems). For small instances, most of the values achieved the optimal makespan value, and, when compared to the metaheuristic ant colony optimization (ACOII) algorithm referred to in the literature, it was found that there were no significant differences between the two methods. However, in terms of large instances, there were significant differences between the optimal makespan obtained by the two methods, revealing overall better performance by the genetic algorithm for Dominant S and Dominant P problems.

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“…In addition, it has been an area of great importance in research, expressed through a vast set of scientific publications [2][3][4][5]. Aydilek et al [10] address a scheduling problem to minimize order delays, in which the configuration times independently of the order processing times, with the application of algorithms of self-adaptive Differential Evolution and a hybrid and simulated insertion algorithm. The scheduling problem with different approaches to change or setup times, with the objective of reducing complexity in order to minimize the makespan or the total production time, with the application of an enhanced version of the ant colony optimization algorithm was studied in [11,12].…”

Section: Introductionmentioning

confidence: 99%

Application of the Simulated Annealing Algorithm to Minimize the makespan on the Unrelated Parallel Machine Scheduling Problem with Setup Times

Amaral

Costa

Rocha

et al. 2019

Advances in Intelligent Systems and Computing

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In this paper, the unrelated parallel machine scheduling problem considering machine-dependent and job sequence-dependent setup times is addressed. This problem involves the scheduling of n jobs on m unrelated machines with setup times in order to minimize the makespan. The Simulated Annealing algorithm is used to solve four sets of small scheduling problems, from the literature, on two unrelated machines: the first one has six jobs, the second has seven jobs and the third and fourth has eight and nine jobs, respectively. The results seem promising when compared with other methods referred in literature.

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Minimising maximum tardiness in assembly flowshops with setup times

Cited by 13 publications

References 28 publications

An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading

An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading

A Statistical Comparison of Metaheuristics for Unrelated Parallel Machine Scheduling Problems with Setup Times

Application of the Simulated Annealing Algorithm to Minimize the makespan on the Unrelated Parallel Machine Scheduling Problem with Setup Times

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