Agent-based simulation and optimization of hybrid flow shop considering multi-skilled workers and fatigue factors

Liu, Youshan; Shen, Weiming; Zhang, Chunjiang; Sun, Xueyan

doi:10.1016/j.rcim.2022.102478

Cited by 25 publications

(3 citation statements)

References 31 publications

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“…Qi et al considered job family and sequence-dependent setup times for the HFSP and developed a MIP and an IG algorithm [42]. Liu et al considered multiskilled workers and fatigue factors for the HFSPs and developed simulation-based optimization (SBO) to solve these problems [43]. Other HFSPs involving different constraints can be found in [44].…”

Section: Literature Reviewmentioning

confidence: 99%

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

2023

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This paper considers the hybrid flow shop scheduling problem, where jobs are processed in m stages with the same route of the stage. Each stage has identical parallel machines for processing jobs. Some mathematical programming formulations and lower bound calculations have been proposed in the literature for such cases. Nevertheless, there is a lack of complete comparisons of these mathematical programming formulations and lower bounds in the hybrid flow shop literature. In this paper, we propose a new mixed integer programming model and two new lower bounds based on the bin-packing concept for the considered problem. To evaluate the proposed model, two sets of small and small-to-medium problems are used to compare our model with the existing models. Moreover, two propositions are discussed for lower bounds. The experimental results show that the proposed mixed integer programming model efficiently found optimal solutions because it needs a smaller number of binary variables and a smaller number of constraints, and the proposed lower bound can also serve as a strong indicator to evaluate the distances between the solutions obtained by heuristic algorithms and the optimal solution.INDEX TERMS hybrid flow shop, makespan, mixed integer programming, lower bound

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Section: Literature Reviewmentioning

confidence: 99%

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

2023

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“…In this improved version, crossover and mutation operations were introduced to enhance the search capability of the cuckoo algorithm by replacing long and short flight strategies. An FFSP problem taking into account human factors effect is studied in [27]. The two considered human factors are the fatigue factor and the multi-skilled workers.…”

Section: Ffsp Recent Publicationsmentioning

confidence: 99%

Effective Two-Phase Heuristic and Lower Bounds for Multi-Stage Flexible Flow Shop Scheduling Problem with Unloading Times

Hidri

2023

Symmetry

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This paper addresses the flexible flow shop scheduling problem with unloading operations, which commonly occurs in modern manufacturing processes like sand casting. Although only a few related works have been proposed in the literature, the significance of this problem motivates the need for efficient algorithms and the exploration of new properties. One interesting property established is the symmetry of the problem, where scheduling from the first stage to the last or vice versa yields the same optimal solution. This property enhances solution quality. Considering the problem’s theoretical complexity as strongly NP-Hard, approximate solutions are preferable, especially for medium and large-scale instances. To address this, a new two-phase heuristic is proposed, consisting of a constructive phase and an improvement phase. This heuristic builds upon an existing efficient heuristic for the parallel machine-scheduling problem and extends it to incorporate unloading times efficiently. The selection of the two-phase heuristic is justified by its ability to generate high-quality schedules at each stage. Moreover, new efficient lower bounds based on estimating minimum idle time in each stage are presented, utilizing the polynomial parallel machine-scheduling problem with flow time minimization in the previous stage. These lower bounds contribute to assessing the performance of the two-phase heuristic over the relative gap performance measure. Extensive experiments are conducted on benchmark test problems, demonstrating the effectiveness of the proposed algorithms. The results indicate an average computation time of 9.92 s and a mean relative gap of only 2.80% for several jobs up to 200 and several stages up to 10.

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“…Glock et al 7 proposed an accumulation function of fatigue as an exponentially increasing function of time. Liu et al 38 developed an agent‐based simulation system to handle uncertainties in the worker fatigue model. They utilized a novel simulation‐based optimization (SBO) framework that combines genetic algorithm (GA) and reinforcement learning (RL) to address the hybrid flow shop scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective optimization allocation of multi‐skilled workers considering the skill heterogeneity and time‐varying effects in unit brake production lines

Zeng,

Nie

2023

Engineering Reports

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The optimal allocation of multi‐skilled workers in labor‐intensive industries can improve production capacity and reduce production costs. In actual production, the efficiency of workers will change with time due to their proficiency, fatigue, and other effects. In this article, we attempt to solve the problem of multi‐skilled workers allocation in unit brake production lines considering the heterogeneity of skills and time‐varying effects. A nonlinear mixed‐integer programming model is established, which fully considers the impact of worker efficiency due to proficiency, fatigue, and multi‐task rest recovery. The product production cycle and worker cost are the two objectives of the optimization solution. An enhanced NSGA‐II algorithm that combines the improved NSGA‐II algorithm and the variable neighborhood search (VNS) algorithm is used to solve the multiobjective optimization problem. Finally, the weighted ideal point method is used to obtain the Pareto optimal solution. The application case of a unit brake production is considered to evaluate the proposed model. The results indicate that the time cost and salary cost of workers are reduced by 8.03% and 18.91% compared with the original scheduling. The scheduling model considering learning, fatigue and recovery factors is more suitable for the actual production situation, ensuring the completion time and reducing the labor cost.

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Agent-based simulation and optimization of hybrid flow shop considering multi-skilled workers and fatigue factors

Cited by 25 publications

References 31 publications

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

Effective Two-Phase Heuristic and Lower Bounds for Multi-Stage Flexible Flow Shop Scheduling Problem with Unloading Times

Multiobjective optimization allocation of multi‐skilled workers considering the skill heterogeneity and time‐varying effects in unit brake production lines

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