Heuristics for the two‐machine scheduling problem with a single server

Arnaout, Jean-Paul

doi:10.1111/itor.12302

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…Of course, it would be of great interest to study the calibration engineer scheduling problem in distributed multiple‐machine settings where several calibration engineers are available. It is also worth considering the coordination of machine calibrations in some stages or machines of a flow shop (Ferone et al., 2020; de Siqueira et al., 2020; Hakeem‐Ur‐Rehman et al., 2021), a job shop (Benttaleb et al., 2019; Abedi et al., 2020; Ham, 2020), or a parallel machine setting where a server is in charge of setups (Arnaout, 2017; Bektur and Saraç, 2019; Krim et al., 2020) such that the production runs smoothly from an overall perspective.…”

Section: Discussionmentioning

confidence: 99%

Short‐term scheduling with machine calibration

Zhao

et al. 2021

Int Trans Operational Res

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In most of the past research on scheduling, it is conventional to model machine deterioration by decreasing production speed over time. However, as is observed, there is a fair number of scenarios in practice where deterioration has a little impact on machine speed but a great impact on production accuracy and a machine is unusable unless it has been calibrated recently. In this paper, we consider a single-machine short-term scheduling issue in distributed production systems where the engineer calibrates the machines in a round-robin manner. The objective is to minimize total job completion time, which is a popular criterion indicating total holding or inventory cost. We consider two cases of the problem and show that one of them can be solved optimally by providing an extended shortest processing time first rule. As for the other case, which is intractable, we propose a polynomial-time approximation scheme based on the extended rule and an exchange procedure. Computational experiments show that the proposed polynomial-time approximation scheme is very promising even if limited number of exchangeable jobs is allowed.

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Section: Discussionmentioning

confidence: 99%

Short‐term scheduling with machine calibration

Zhao

et al. 2021

Int Trans Operational Res

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“…Further research may focus on problems with some other criteria such as minimizing total completion time (Parsa et al., 2019; Zhu et al., 2019) and maximizing the noon break period under a given deadline for all the jobs or problems in some other production environments such as flow shop (Hakeem‐Ur‐Rehman et al., 2019; Krim et al., 2019b; Ferone et al., 2020; de Siqueira et al., 2020), job shop (Benttaleb et al., 2018, 2019; Kubiak et al., 2020), and parallel machine with a single server (Arnaout, 2017; Bektur and Saraç, 2019). It is also worth considering scheduling problems in industries that are open around the clock, such as in airports, restaurants, hospitals, movie theaters, and in some retail stores, where morning, afternoon, and night shifts are involved.…”

Section: Discussionmentioning

confidence: 99%

Scheduling with day shifts and breaks

2020

Int Trans Operational Res

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Traditional scheduling assumes that production can continue around the clock unless machines are not available. This is not without question for labor-intensive industries where operations are performed manually. Motivated by operation management problems arising in the assembly stage of aeroengines and in the paintspraying stage of wooden furniture, we consider a scheduling problem with day shifts and breaks. We transform the problem into a new bin-packing problem and present some theoretical analyses. To meet the needs of practical applications, we propose a binary integer programming (BIP) formulation and a hybrid genetic algorithm (HGA) that is based on five heuristic algorithms and two postoptimization procedures. Computational results indicate that the BIP formulation is suitable for some data sets while the HGA is the most promising in that it saves about 37% of day shifts compared to the best of the five heuristic algorithms in the context of scheduling.

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“…I-L algorithm was also used for instances of 10,000 jobs (with a runtime of 371.3s). [41] proposed an ant colony optimization (ACO) algorithm and assessed the ACO performance with branch and bound with instances up to 100 jobs. In addition, ACO algorithm was assessed with instances up to 1,000 jobs and compared its results with GA and SA algorithms results reported in [39].…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

et al. 2021

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In this study, the objective of minimizing makespan has been considered for a scheduling problem of identical parallel machines with a single server and unavailability constraints. The unavailability constraints correspond to preventive maintenance periods. In this study, the jobs and the maintenance periods are scheduled simultaneously. This scheduling problem has a wide range of potential application areas in the manufacturing environment. In addition, the studied problem is a challenging one from theoretical point of view, due to its NP-Hardness. To conduct the study, a lower bound (LB) for the problem, and three metaheuristics namely Simulated Annealing (SA), Tabu Search (TS), and Genetic Algorithm (GA) have been proposed. The best parameters settings of the proposed algorithms were conducted using pilot runs with a Taguchi design. The algorithms performance has been assessed by using a set of test problems generated randomly. These test problems are based on a literature benchmark. The size of the instances, or number of jobs, were up to 500. Along with the performance analysis of the proposed algorithms, the effect of varying processing times and unavailability periods on the performance of the proposed algorithms is studied. The present work provides strong evidence of the efficiency and the performance of the proposed algorithms.

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Heuristics for the two‐machine scheduling problem with a single server

Cited by 11 publications

References 11 publications

Short‐term scheduling with machine calibration

Short‐term scheduling with machine calibration

Scheduling with day shifts and breaks

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

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