Neural Computing and Applications

, Volume 31, Supplement 1, pp 347–357 | Cite as

Type II assembly line balancing problem with multi-operators

  • Yuchen Li
  • Honggang Wang
  • Zaoli YangEmail author
Machine Learning Applications for Self-Organized Wireless Networks


In this paper, we present a practical line balancing problem: multiple-operator assembly line balancing problem II. The formulation of the proposed problem is novel in terms of investigating the operator assignment from a different perspective. In order to solve this problem, we develop a simulated annealing (SA)-based two-stage solution procedure, where a new neighborhood generation and a search method are designed and demonstrated to be more efficient than the traditional neighborhood search method. In theory, we prove the original neighborhood generation method is not efficient than the proposed one. Computational experiments on some benchmark cases have been conducted to validate the efficiency of the proposed algorithm compared to the traditional SA approach. Our work also has some practical merits. In the managerial situation, a factory may have already recruited some workers that cannot be dismissed. Our problem describes that the production manager allocates different number of workers to the workstations to minimize the cycle time.


Assembly line balancing Parallel stations Simulated annealing Multiple-operator assignments Feasible neighborhood generation 



Funding was provided by National Natural Science Funds of China (Grant No. 71704007).


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research Base of Beijing Modern Manufacturing Development, School of Economics and ManagementBeijing University of TechnologyBeijingChina
  2. 2.College of Business and Public ManagementUniversity of La VerneLa VerneUSA

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