Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210900165-5.doi: 10.11896/jsjkx.210900165

• Artificial Intelligence • Previous Articles     Next Articles

Improved Ant Colony Algorithm for Solving Multi-objective Unilateral Assembly Line Balancing Problem

WU Xiao-wen1, ZHENG Qiao-xian1, XU Xin-qiang2   

  1. 1 College of Computer and Information Engineering,Hubei University,Wuhan 430062,China
    2 School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:WU Xiao-wen,born in 1998,postgra-duate.Her main research interests include intelligent algorithm and deep learning.
  • Supported by:
    Natural Science Foundation of China(61803149) and Feasibility Theory and High Precision Adaptive Heuristic Algorithm for Multi Constraint Assembly Balance Problem(61803149003593).

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Abstract: In response to the second type of unilateral assembly line balance in industrial production,it is established with minimal chemical sections under two constraints.In these two constraints,Mathematical model for optimizing the balance loss rate.A feasible solution to the unilateral assembly line balance problem using an improved ant colony algorithm combining ant colony algorithm and simulated annealing algorithm.The algorithm uses the operation selection mechanism and the operation allocation mechanism to select and assign it to a station.In the experiment,simulation examples are used to verify the feasibility of the algorithm,and 8 examples are used to verify the effectiveness of the proposed algorithm for solving the problem,and to produce certain technical method support for actual industrial production.

Key words: Ant colony algorithm, Simulated annealing algorithm, Multi-objective, Unilateral assembly line balancing problem

CLC Number: 

  • TP311
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