Improved cuckoo optimization algorithm for human-machine collaborative disassembly line balancing problem

Zhe Xing; YunPing Han; Jiacun Wang; Shujin Qin; Liang Qi; Yuanyuan Tan

doi:10.1117/12.2656847

20 October 2022 Improved cuckoo optimization algorithm for human-machine collaborative disassembly line balancing problem

Zhe Xing, YunPing Han, Jiacun Wang, Shujin Qin, Liang Qi, Yuanyuan Tan

Author Affiliations +

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124514F (2022) https://doi.org/10.1117/12.2656847
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

With the aggravation of environmental pollution, how to solve the problem of waste recycling is particularly important. Product disassembly is a vital part of waste recycling. Reasonable and efficient recycling can create economic benefits while protecting the environment. Therefore, disassembly lines have been established and widely used. In this paper, a human-machine collaborative disassembly line balancing problem considering maximizing economic benefits is studied. A linear mathematical model is established, and the correctness of the model is verified. An improved cuckoo search algorithm is proposed in this paper. Experimental results show that the algorithm has higher efficiency in large-scale disassembly problems while ensuring optimal solutions.

Citation Download Citation

Zhe Xing, YunPing Han, Jiacun Wang, Shujin Qin, Liang Qi, and Yuanyuan Tan "Improved cuckoo optimization algorithm for human-machine collaborative disassembly line balancing problem", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124514F (20 October 2022); https://doi.org/10.1117/12.2656847

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available