New chance-constrained models for U-type stochastic assembly line balancing problem

Pınarbaşı, Mehmet

doi:10.1007/s00500-021-05921-z

Cited by 10 publications

(11 citation statements)

References 37 publications

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“…Zhang et al (2020) designed a restarted iterated Pareto greedy algorithm to optimize minimize cycle times and ergonomic risks. Pinarbasi (2021) proposed two new chance-constrained nonlinear model to solve stochastic UAL balancing.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Modeling and solving the two-sided U-type assembly line balance based on a heuristic algorithm of a multi-priority rule

Jiao

Deng

et al. 2022

Concurrent Engineering

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In order to improve the efficiency of assembly line and optimize the layout, this paper presents a collaborative optimization model for a two-sided U-type assembly line and a novel design with p-l partition layout is proposed to minimize number of workstations without increasing the length of the assembly line. Considering the task orientation and time sequencing in cross-workstation, the mathematical model of two-sided U-type assembly line balancing problem is derived. A multi-level priority rule heuristic algorithm is developed to drive the optimization process. The multi-level priority rule heuristic algorithm, modified particle swarm optimization algorithm, and the bi-objective integer programming method are applied to 20 classic examples, respectively. The calculation results suggest that the optimal results of the proposed method account for 90%, which verifies the rationality of the collaborative optimization model and algorithm, and provides a useful reference for the modeling and solution of the two-sided U-type assembly line balancing problems.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Modeling and solving the two-sided U-type assembly line balance based on a heuristic algorithm of a multi-priority rule

Jiao

Deng

et al. 2022

Concurrent Engineering

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show abstract

“…The problems vary in their sizes from 7 to 148 tasks. The comparison is done with a constrained programming approach (CP) proposed by Pınarbaşı (2021). The problems in the benchmark are deterministic.…”

Section: Computational Resultsmentioning

confidence: 99%

“…Therefore, this paper presents one of the uncertainty cases of the problem, which is the chance-constrained problem. In addition, it proposes an efficient GRASP algorithm as a new approach for solving the problem, where its results are compared with the results found in (Pınarbaşı, 2021) and proofed a high efficiecy in terms of objective values and CPU times.…”

Section: Literature Reviewmentioning

confidence: 94%

“…Aydoğan et al (2019) developed a particle swarm optimization algorithm to minimize the number of stations under uncertainty. Pınarbaşı (2021) dealt with the same problem discussed in this paper through linearinzing the non-linear constraints and he used IBM ILOG CP solver to solve them.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The selected problems of for computational results are solved in case that the chance probabilities are equal to 0.90, 0.95, and 0.975. To proof the efficiency of the proposed GRASP algorithm, the computational results is compared with the results of constrained programming approach found in (Pınarbaşı, 2021). The paper is organized as follows: the second section presents a literature review of the U-shaped assembly line balancing problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Greedy Randomized Adaptive Search for Solving Chance-Constrained U-Shaped Assembly Line Balancing Problem

Zakaraia

Zaher

Ragaa

2022

International Journal of Applied Metaheuristic Computing

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This paper discusses the U-shaped assembly line balancing problem in case of stochastic processing time. The problem is formulated using chance-constrained programming and the greedy randomized adaptive search procedure is used to solve the problem. In order to prove the efficiency of the proposed algorithm, 71 problems taken from well-known benchmarks are solved and compared with the theoretical lower bound and 13 of them were compared with another approach used to solve the same problem in another paper, which is beam search. The results show that 59 problems are the same as the theoretical aspiration lower bound. In addition, the results of 11 of 13 problems compared with beam search are the same and the results of 2 problems are better than beam search. The t-test statistics is applied and showed that there is no significance difference between the proposed algorithm and the theoretical lower bound thus, the proposed algorithm shows efficiency when compared with the aspired values of the theoretical lower bound.

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Balancing of cost-oriented U-type general resource-constrained assembly line: new constraint programming models

Alakaş

Pınarbaşı

2023

Soft Comput

Self Cite

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In simple assembly line balancing problems, it is assumed that the resources required to perform the tasks are available at the relevant station for task assignment. However, each task may need different resource types depending on the difficulty, complexity and technical requirements of the tasks in real life. For this reason, tasks and resources belonging to these tasks must be assigned to the relevant station while balancing the line. In this study, the resource-constrained U-shaped assembly line balancing problem(U-GRCALBP) is discussed. According to the literature research, there is no study dealing with U-GRCALBP. Two different constraint programming (CP) models that define the resource constraints as "and/or" constraint types with concurrent resource types have been developed. In these models, the sum of resource usage costs and station opening cost minimization is aimed. The models are explained with an illustrative example and the efficiency of the models was tested by deriving new resource constraints on sample data sets. The number of stations obtained, the total number of resources used, total station opening and resource usage costs, and CPU time were used as performance criteria. According to the numerical results, it has been shown that both models are effective in solving the problem.

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New chance-constrained models for U-type stochastic assembly line balancing problem

Cited by 10 publications

References 37 publications

RETRACTED: Modeling and solving the two-sided U-type assembly line balance based on a heuristic algorithm of a multi-priority rule

RETRACTED: Modeling and solving the two-sided U-type assembly line balance based on a heuristic algorithm of a multi-priority rule

A Greedy Randomized Adaptive Search for Solving Chance-Constrained U-Shaped Assembly Line Balancing Problem

Balancing of cost-oriented U-type general resource-constrained assembly line: new constraint programming models

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