Simultaneous machine selection and buffer allocation in large unbalanced series-parallel production lines

Xi, Shao-Hui; Smith, J. MacGregor; Chen, Qingxin; Mao, Ning; Zhang, Hui-Yu; Yu, Ao

doi:10.1080/00207543.2021.1884306

Cited by 19 publications

(17 citation statements)

References 70 publications

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“…the number of machines allocated to each workstation). The literature shows that the combinatorial complexity of each of the three allocation problems is NP-hard (Xi et al 2022 ). Furthermore, as the size of the problem increases, the computational complexity of the problem increases considerably.…”

Section: Literature Reviewmentioning

confidence: 99%

Simultaneous allocation of buffer capacities and service times in unreliable production lines

Kassoul

Cheikhrouhou

Zufferey

2023

International Journal of Production Research

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Simultaneous allocation of service times and buffer capacities in manufacturing systems in a random environment is a NP-hard combinatorial optimisation problem. This paper presents a sophisticated simulation-based optimisation approach for the design of unreliable production lines to maximise the production rate. The proposed method allows for a global search using a Genetic Algorithm (GA), which is coupled with Finite Perturbation Analysis (FPA) as a local search technique. Traditional techniques based on perturbation analysis optimise decision variables of the same nature (e.g. service time only, buffer capacity only), whereas the proposed technique simultaneously provides an allocation of service times and buffer capacities. One of the main focuses of this paper is the investigation of the persistence or absence of the buffer and service rate allocation patterns which are among the most essential insights that come from designing production lines. The results show the superiority of the combined GA-FPA approach regarding GA and FPA in terms of solution quality and convergence behaviour. Moreover, considering instances ranging from 3 to 100 machines, our numerical experiments are in line with the literature for small instances (as similar allocation patterns are identified in our work), but important differences are highlighted for medium/large instances.

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Section: Literature Reviewmentioning

confidence: 99%

Simultaneous allocation of buffer capacities and service times in unreliable production lines

Kassoul

Cheikhrouhou

Zufferey

2023

International Journal of Production Research

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“…[15][16][17] Yelkenci Kose and Kilincci 18 proposed a simulated annealing (SA) based nondominated sorting genetic algorithm II (NSGA-II) to maximize the average system throughput and minimize the total buffer size. Xi et al 19 developed a decomposition coordination method to minimize the total cost investment by allocating buffers and machines and selecting machine types. Despite the rich number of previous studies on metaheuristics, the performance of a metaheuristic algorithm highly depends on the problem being handled.…”

Section: Introductionmentioning

confidence: 99%

A data-driven ensemble algorithm of black widow optimizer and simulated annealing algorithms for multi-objective buffer allocation in production lines

Gao

Liu

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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The multi-objective buffer allocation problem of production lines is a non-deterministic-polynomial-hard problem. Many metaheuristic algorithms have been proposed to solve this problem. However, further investigation of new algorithms is still required because metaheuristic algorithms highly depend on the problem types. Furthermore, the balance between the solution quality and computational efficiency requires further improvement. Therefore, a data-driven algorithm consisting of the black widow optimizer and simulated annealing algorithm is proposed to maximize throughput and minimize energy consumption in production lines. Numerical examples demonstrate that the proposed algorithm achieves better solution quality than other state-of-the-art algorithms without losing computational efficiency. This study contributes to multi-objective optimization of resource scheduling in production lines.

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“…Shi and Gershwin in [12] developed a segmentation approach, but the method is not ideal inaccuracy. Based on the segmentation approach, Xi et al proposed a method in [13] to solve BAP for unbalanced series-parallel production lines. Alfieri and Matta in [14] present a time-based decomposition algorithm to split the mathematical programming model into sub-models that are solved sequentially.…”

Section: Introductionmentioning

confidence: 99%

The hierarchical decomposition parallel optimizing technique for large-scale production lines

Hao

Ren

2022

Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022)

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The scheduling problems of production lines like buffer allocation problems (BAP) are usually NP-Hard problems and are complex to deal with using traditional techniques, especially for large-scale production lines disturbed by such stochastic events as the breakdown of machines. For large-scale production lines consisting of unreliable machines, the hierarchical decomposition parallel optimizing technique (HDPOT) is proposed here. The technique combines with the aggregation method of the hybrid production line to decompose the original production line into 1 n  subsystems by following some principles. Moreover, the asymptotic optimum solution of the original production line is gotten by searching parallel the optimum solutions of the subsystems. Meanwhile, an improved simulated annealing algorithm is proposed for the parallel optimization of subsystems. The HDPOT finally is tested by an example of buffer allocation problems (BAP) and specified by numerical experiments. The results show that this technique can solve scheduling problems more accurately, especially for large-scale production lines.

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Simultaneous machine selection and buffer allocation in large unbalanced series-parallel production lines

Cited by 19 publications

References 70 publications

Simultaneous allocation of buffer capacities and service times in unreliable production lines

Simultaneous allocation of buffer capacities and service times in unreliable production lines

A data-driven ensemble algorithm of black widow optimizer and simulated annealing algorithms for multi-objective buffer allocation in production lines

The hierarchical decomposition parallel optimizing technique for large-scale production lines

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