Reducing the total tardiness by <i>Seru</i> production: model, exact and cooperative coevolution solutions

Sun, Wei; Yu, Yang; Lou, Qi; Wang, Junwei; Guan, Yuechao

doi:10.1080/00207543.2019.1680898

Cited by 29 publications

(16 citation statements)

References 35 publications

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“…The following assumptions are made for the divisional seru manufacturing system: the type and batch of the product are known; the cost of new equipment and tools is ignored; in the assembly line, each worker performs only one process, so the number of workers (W) Is equal to the number of processes; The number of workers in different seru can be different; The assembly tasks in each divided seru are the same as the assembly tasks in the assembly line; The interval between adjacent batches of different types of products is heavy Set time, the interval between adjacent batches of the same product is 0. is the start processing time of the batch of products in the seru as shown in Equation (5).…”

Section: Assumptionmentioning

confidence: 99%

“…Kaku et al, built two goals in the model (total production time and total man-hours), and experiments based on numerical simulations were performed to analyze the effects of various operating factors on the line-battery conversion [3]. Reducing workers can address labor costs.…”

Section: Introductionmentioning

confidence: 99%

“…However, when considering these two goals at the same time, the Pareto optimal solution may save manpower but increase the validity period. At the same time, the algorithm is suitable for use when the workers are small [5].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Research on Personnel Allocation Strategies of Reducing Workers in Divisional Seru

Li¹,

Wen²,

Hou³

et al. 2020

dtetr

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With the diversification and individual development of the economy, enterprise competition tends to be international, and traditional production line has disadvantages in terms of efficiency and labor costs. This paper considers reducing workers to reduce labor costs in line-seru. It also considers reducing the number of workers without increasing the manufacturing period of the product to ensure timely delivery. This paper proposes a multi-objective model to solve the problem of reducing the number of workers and not increasing the manufacturing period. The variable length coding heuristic algorithm is used to solve the model. This algorithm is not only suitable for the case of fewer workers, but also has good applicability to medium and large-scale problems.

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Section: Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Research on Personnel Allocation Strategies of Reducing Workers in Divisional Seru

Li¹,

Wen²,

Hou³

et al. 2020

dtetr

View full text Add to dashboard Cite

show abstract

“…For seru scheduling, there are few studies [13,18]. Yu et al selected ten usually used scheduling rules to investigate the performance of different rules on the line-seru conversion problem.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Heuristic Design Approach for Seru Scheduling Problem with Resource Conflicts

Zhan

Zhang

Cui³

et al. 2021

Discrete Dynamics in Nature and Society

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In current environments, production systems need the ability of quick response to face the volatile markets. Seru production systems, as a new mode of the production system, have the advantages of quick response, high flexibility, and high efficiency. Seru scheduling, which refers to constructing serus with an exact sequence in limited workspace, is an important decision problem in the operational management of seru production systems and can reflect the reconfiguration nature of seru production systems. This study investigates a seru scheduling problem with resource conflicts, whose objective is to minimize the makespan. An automatic heuristic design approach that combines a genetic programming algorithm and structure similarity-based operators is proposed. Comparative experiments are conducted with human-made rules, basic genetic programming, genetic programming-based algorithm, and with some state-of-the-art scheduling algorithms. The results show the effectiveness and efficiency of the proposed algorithm.

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“…Sun et al (2019) [41] developed a cooperative coevolution algorithm which combining generic algorithm and local search, and the ant colony optimization algorithm for solving seru formulation and seru scheduling problem at the same time with the objective of minimizing makespan. Sun et al (2019) [42] used a cooperative coevolution algorithm to solve seru production problem aim at reducing the total tardiness. Although the researches above took worker assignment into account, few researches has considered the hierarchy of worker assignment decision and production allocation decision.…”

mentioning

confidence: 99%

Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems

Luo¹,

Zhang²,

Yin³

2021

Journal of Industrial &Amp; Management Optimization

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Seru production is one of the latest manufacturing modes arising from Japanese production practice. Seru can achieve efficiency, flexibility, and responsiveness simultaneously. To accommodate the current business environment with volatile demands and fierce competitions, seru has attracted more and more attention both from researchers and practitioners. A new planning management system, just-in-time organization system (JIT-OS), is used to manage and control a seru production system. The JIT-OS contains two decisions: seru formation and seru loading. By seru formation, a seru system with one or multiple appropriate serus is configured; by seru loading, customer ordered products are allocated to serus to implement production plans. In the process of seru formation, workers have to be assigned to serus. In this paper, a seru loading problem with worker assignment is constructed as a bi-level programming model, and the worker assignment on the upper level is to minimize total idle time while the lower level is to minimize the makespan by finding out optimal product allocation. A product lot can be splitted and allocated to different serus. The problem of this paper is shown to be NP-hard. Therefore, a simulated annealing and genetic algorithm (SA-GA) is developed. The SA is for the upper level programming and the GA is for the lower level programming. The practicality and effectiveness of the model and algorithm are verified by two numerical examples, and the results show that the SA-GA algorithm has good scalability.

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Reducing the total tardiness by Seru production: model, exact and cooperative coevolution solutions

Cited by 29 publications

References 35 publications

Research on Personnel Allocation Strategies of Reducing Workers in Divisional Seru

Research on Personnel Allocation Strategies of Reducing Workers in Divisional Seru

An Automatic Heuristic Design Approach for Seru Scheduling Problem with Resource Conflicts

Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems

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