A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem

Zacharia, Paraskevi Th.; Nearchou, Andreas C.

doi:10.1016/j.engappai.2015.11.007

Cited by 60 publications

(29 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent surveys of the results in this field are given by Battaïa and Dolgui [6], Battaïa et al [5], De Bruecker et al [16] and Dolgui et al [17]. Further information can be found in Vairaktarakis et al [42], Polat et al [32], Dalle Mura and Dini [14], Yilmas and Yilmas [47], Zacharia and Nearchou [48] and Ritt et al [34].…”

Section: Literature Reviewmentioning

confidence: 99%

Minimizing the number of workers in a paced mixed-model assembly line

Delorme

Dolgui

Kovalev

et al. 2019

European Journal of Operational Research

View full text Add to dashboard Cite

We study a problem of minimizing the maximum number of identical workers over all cycles of a paced assembly line comprised of m stations and executing n parts of k types. There are lower and upper bounds on the workforce requirements and the cycle time constraints. We show that this problem is equivalent to the same problem without the cycle time constraints and with fixed workforce requirements. We prove that the problem is NP-hard in the strong sense if m = 3 and if m = 4 and the workforce requirements are station independent, and present an Integer Linear Programming model, an enumeration algorithm and a dynamic programming algorithm. Polynomial in k and polynomial in n algorithms for special cases with two part types or two stations are also given. The relation to the Bottleneck Traveling Salesman Problem and its generalizations are discussed.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Minimizing the number of workers in a paced mixed-model assembly line

Delorme

Dolgui

Kovalev

et al. 2019

European Journal of Operational Research

View full text Add to dashboard Cite

show abstract

“…Due to the superiority of the new proposed algorithm, it is suggested to utilize this new algorithm to solve different or more complex assembly line balancing problems, such as mixed-model robotic assembly line (Aghajani et al, 2014;Li et al, 2017b), worker assignment (Zacharia and Nearchou, 2016) and parallel workstations (Akpınar and Mirac Bayhan, 2011). Since the real industrial contexts are diverse and more complex, another interesting avenue is related to the robotic assembly line itself by involving more realistic features.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Janardhanan

Ashour

et al. 2019

Neural Comput & Applic

View full text Add to dashboard Cite

Modern assembly line systems utilize robotics to replace human resources to achieve higher level of automation and flexibility. This work studies the task assignment and robot allocation in a robotic U-shaped assembly line. Two new mixed integer programming linear models are developed to minimize the cycle time when the number of workstations is fixed. Recently developed migrating birds optimization (MBO) algorithm is employed and improved to solve large-sized problems. Problemspecific improvements are also developed to enhance the proposed algorithm including modified consecutive assignment procedure for robot allocation, iterative mechanism for cycle time update, new population update mechanism and diversity controlling mechanism. An extensive comparative study is carried out to test the performance of the proposed algorithm, where seven high-performing algorithms recently reported in the literature are re-implemented to tackle the considered problem. The computational results demonstrate that the developed models are capable to achieve the optimal solutions for small-sized problems, and the proposed algorithm with these proposed improvements achieves excellent performance and outperforms the compared ones.

show abstract

“…Ritt et al (2016) consider uncertain worker availability in ALWABP and propose local search heuristics. Zacharia and Nearchou (2016) tackle the bi-objective ALWABP using a multiobjective evolutionary algorithm to minimize the cycle time and smoothness index. Akyol and Baykasoğlu (2016) solve ALWABP using a multiple-rule-based constructive randomized search (MRBCRS) algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Model and migrating birds optimization algorithm for two-sided assembly line worker assignment and balancing problem

Janardhanan

Nielsen

2018

Soft Comput

View full text Add to dashboard Cite

Worker assignment is a relatively new problem in assembly lines that typically is encountered in situations in which the workforce is heterogeneous. The optimal assignment of a heterogeneous workforce is known as the assembly line worker assignment and balancing problem (ALWABP). This problem is different from the well-known simple assembly line balancing problem concerning the task execution times, and it varies according to the assigned worker. Minimal work has been reported in worker assignment in two-sided assembly lines. This research studies worker assignment and line balancing in two-sided assembly lines with an objective of minimizing the cycle time (TALWABP). A mixed-integer programming model is developed, and CPLEX solver is used to solve the small-size problems. An improved migrating birds optimization (MBO) algorithm is employed to deal with the large-size problems due to the NP-hard nature of the problem. The proposed algorithm utilizes a restart mechanism to avoid being trapped in the local optima. The solutions obtained using the proposed algorithms are compared with well-known metaheuristic algorithms such as artificial bee colony and simulated annealing. Comparative study and statistical analysis indicate that the proposed algorithm can achieve the optimal solutions for small-size problems, and it shows superior performance over benchmark algorithms for large-size problems.

show abstract

A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem

Cited by 60 publications

References 31 publications

Minimizing the number of workers in a paced mixed-model assembly line

Minimizing the number of workers in a paced mixed-model assembly line

Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Model and migrating birds optimization algorithm for two-sided assembly line worker assignment and balancing problem

Contact Info

Product

Resources

About