The single machine scheduling problem with setup times under an extension of the general learning and forgetting effects

Muştu, Settar; Eren, Tamer

doi:10.1007/s11590-020-01641-9

Cited by 15 publications

(4 citation statements)

References 41 publications

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“…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. Mutu and Eren (2020) studied the single machine scheduling problem with sequenceindependent setup times and time-dependent learning and forgetting effects. Aldowaisan and Allahverdi (2015) proposed an improved genetic algorithm and an improved simulated annealing algorithm for the flow shop scheduling problem where the sequenceindependent setup time is considered.…”

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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“…For the proposed system, their experimental results indicated a better and fairer distribution of energy expenditure among workers. Some researchers have investigated some human factors like fatigue in project scheduling, 40 fatigue and learning in the field of human-robot collaboration, 41 work motivation in job rotation, 42 learning and forgetting effects on machine scheduling problem [43][44][45][46] and human factors in the problem of fuzzy integrated cell formation and production scheduling with guided vehicles. 47 The survey of the previous studies indicates that no paper examined the effects of human factors of learning, forgetting, fatigue, and rest at the same time on the human reliability in the field of shift scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing human reliability in work shifts scheduling: A real case of clothing job shop

Arekamari

Namaghi

2023

Quality & Reliability Eng

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In this research, we provide a mathematical model with an objective function of minimizing human errors for the problem of shift scheduling optimization. The unique aspects which are considered in our model are learning, forgetting, fatigue, and rest parameters (which affect the human reliability). Various problems with different human parameters, based on real cases of clothing job shops, are solved to study the efficiency and effectiveness of the optimization model. Two improved bacterial foraging algorithms are presented to handle the complexity of our problem. To examine the capability of the presented swarm intelligence algorithms in obtaining global optimum problem, we compare the results of the algorithms against the solution of basic bacterial foraging algorithm in terms of solutions quality. Results indicate that the solution approaches are more efficient in searching solution space and convergence. Analysis of different shift scheduling shows that in moderate fatigue condition, the scenario of scheduling with continuous work hours is better in terms of productivity. Also, experiments demonstrate that optimum reliable shift schedules are related to human factors. The findings of our research indicate that the presented scheduling model and improved algorithms can provide optimum shift schedules regarding human factors.

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“…More recently, Liu and Jiang [11] addressed single-machine resource allocation scheduling problems with learning effects, where learning effects mean job-dependent position-based learning effects. Additionally, Muştu and Eren [12] addressed the optimization of a singlemachine scheduling cases with setup times under an extension of the general learning and forgetting effects, and the objective function is to minimize the maximum completion time. They proposed an integer non-linear programming model and a dynamic programming model, which can be executed in pseudo-polynomial time.…”

Section: Introductionmentioning

confidence: 99%

Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times

He,

Zhao,

et al. 2023

Mathematics

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In this paper, we study a single-machine green scheduling problem with learning effects and past-sequence-dependent delivery times. The problem can be properly applied to tackle green manufacturing where production and delivery time are variable and highly subject to process-reengineering. Our goal is to determine the optimal sequence such that total weighted completion time and maximum tardiness are minimized. For the general case, we provide the analysis procedure of lower bound, and also propose the heuristic and branch-and-bound algorithms. Furthermore, computational experiments are conducted to demonstrate the effectiveness of our algorithms.

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The single machine scheduling problem with setup times under an extension of the general learning and forgetting effects

Cited by 15 publications

References 41 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

Optimizing human reliability in work shifts scheduling: A real case of clothing job shop

Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times

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