An exact solution method for solving seru scheduling problems with past-sequence-dependent setup time and learning effect

Jiang, Yujing; Zhang, Zhe; Gong, Xue; Yin, Yong

doi:10.1016/j.cie.2021.107354

Cited by 24 publications

(5 citation statements)

References 43 publications

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“…Equation ( 9) represents the number of workers within each seru unit. Equation (10) indicates that each order can only be assigned to one seru unit without considering order splitting. Equation (11) represents the processing time of all products in seru i for order j.…”

Section: Modelingmentioning

confidence: 99%

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Optimizing Production Schedules: Balancing Worker Cooperation and Learning Dynamics in Seru Systems

Liu,

Dai,

Wang

2023

Processes

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This paper aims to investigate the seru scheduling problem while considering the dual effects of worker cooperation and learning behavior to minimize the makespan and order processing time. Given the complexity of this research problem, an improved shuffled frog leaping algorithm based on a genetic algorithm is proposed. We design a double-layer encoding based on the problem, introduce a single point and uniform crossover operator, and select the crossover method in probability form to complete the evolution of the meme group. To avoid damaging grouping information, the individual encoding structure is transformed into unit form. Finally, numerical experiments were conducted using numerical examples of large and small sizes for verification. The experimental results demonstrate the feasibility of the proposed model and algorithm, as well as the necessity of considering worker dual behavior in the seru scheduling problem.

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Section: Modelingmentioning

confidence: 99%

“…In terms of seru scheduling, Zhan et al [9] proposed the GP-SS scheduling rule to address the seru scheduling problem with resource conflicts. Jiang et al [10] transformed the seru scheduling problem into an assignment problem. Li et al [11] studied the on-line seru scheduling problem while considering resource conflicts.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Production Schedules: Balancing Worker Cooperation and Learning Dynamics in Seru Systems

Liu,

Dai,

Wang

2023

Processes

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“…In recent years, the scheduling problem considering the learning effect has attracted increasing attention from scholars. Jiang et al 17 studied seru scheduling problems considering past-sequence-dependent setup times and DeJong’s learning effect. It was shown that relaxing the assumption of the learning coefficients can reduce the complexity of the problem.…”

Section: Introductionmentioning

confidence: 99%

Minimizing the makespan and carbon emissions in the green flexible job shop scheduling problem with learning effects

Li¹,

Chen²

2023

Sci Rep

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One of the most difficult challenges for modern manufacturing is reducing carbon emissions. This paper focuses on the green scheduling problem in a flexible job shop system, taking into account energy consumption and worker learning effects. With the objective of simultaneously minimizing the makespan and total carbon emissions, the green flexible job shop scheduling problem (GFJSP) is formulated as a mixed integer linear multiobjective optimization model. Then, the improved multiobjective sparrow search algorithm (IMOSSA) is developed to find the optimal solution. Finally, we conduct computational experiments, including a comparison between IMOSSA and the nondominated sorting genetic algorithm II (NSGA-II), Jaya and the mixed integer linear programming (MILP) solver of CPLEX. The results demonstrate that IMOSSA has high precision, good convergence and excellent performance in solving the GFJSP in low-carbon manufacturing systems.

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“…For more recent scheduling papers with learning efect, the readers are suggested to refer to the studies by Yang and Lu [16]; Jiang et al [17]; Rudek [18]; Jiang et al [19]; Wu et al [20]; Bai et al [15]; Li et al [9]; and Li et al [21].…”

Section: Introductionmentioning

confidence: 99%

Single‐Machine Group Scheduling Problems with General Deterioration and Linear Learning Effects

Lei

Sun

2023

Mathematical Problems in Engineering

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In this paper, we introduce a group scheduling model with deterioration and a general linear learning effect. The group setup time is a linear deterioration function of its starting time. The general learning effect is time-dependent and position-dependent. The objectives are to minimize the makespan, total completion time, and total weighted completion time, respectively. We show the problems remain solvable in polynomial time under the proposed model.

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An exact solution method for solving seru scheduling problems with past-sequence-dependent setup time and learning effect

Cited by 24 publications

References 43 publications

Optimizing Production Schedules: Balancing Worker Cooperation and Learning Dynamics in Seru Systems

Optimizing Production Schedules: Balancing Worker Cooperation and Learning Dynamics in Seru Systems

Minimizing the makespan and carbon emissions in the green flexible job shop scheduling problem with learning effects

Single‐Machine Group Scheduling Problems with General Deterioration and Linear Learning Effects

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