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Original Article
A Discrete Multi Objective Artificial Bee Colony Algorithm for a Real World Electronic Device Testing Machine Allocation Problem
Liang GAO
Huazhong University of Science and Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0002-1485-0722
License:
This work is licensed under a CC BY 4.0 License. Read Full License
This paper studies the Electronic Device Testing Machine Allocation Problem (EDTMAP), aiming to improve the production of electronic devices and reduce the scheduling distance of testing machines through reasonable machine allocation. Firstly, a mathematical model is formulated for the EDTMAP to maximize both production and the opposite of the scheduling distance of testing machines. Secondly, we develop a Discrete Multi Objective Artificial Bee Colony (DMOABC) algorithm to solve the EDTMAP. A crossover operator and a local search operator are designed to improve the exploration and exploitation of the algorithm, respectively. Some numerical experiments are designed to evaluate the performance of the proposed algorithm. The experimental results demonstrate the superiority of the proposed algorithm compared with NSGA --Ⅱ and SPEA2. Finally, the mathematical model and the DMOABC algorithm are
applied to a real world factory that tests radio frequency modules. The result also verifies our method can significantly improve production and reduce the scheduling distance of testing machines.
Keywords
electronic device, machine allocation, multi-objective optimization, artificial bee colony algorithm
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This preprint is under consideration at Chinese Journal of Mechanical Engineering. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Original Article
A Discrete Multi Objective Artificial Bee Colony Algorithm for a Real World Electronic Device Testing Machine Allocation Problem
Liang GAO
Huazhong University of Science and Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0002-1485-0722
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 20 Jan, 2021
No community comments so far
Editor assigned
On 15 Jan, 2021
Submission checks complete
On 15 Jan, 2021
Editor invited
On 15 Jan, 2021
First submitted
On 12 Jan, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Mechanical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
This paper studies the Electronic Device Testing Machine Allocation Problem (EDTMAP), aiming to improve the production of electronic devices and reduce the scheduling distance of testing machines through reasonable machine allocation. Firstly, a mathematical model is formulated for the EDTMAP to maximize both production and the opposite of the scheduling distance of testing machines. Secondly, we develop a Discrete Multi Objective Artificial Bee Colony (DMOABC) algorithm to solve the EDTMAP. A crossover operator and a local search operator are designed to improve the exploration and exploitation of the algorithm, respectively. Some numerical experiments are designed to evaluate the performance of the proposed algorithm. The experimental results demonstrate the superiority of the proposed algorithm compared with NSGA --Ⅱ and SPEA2. Finally, the mathematical model and the DMOABC algorithm are
applied to a real world factory that tests radio frequency modules. The result also verifies our method can significantly improve production and reduce the scheduling distance of testing machines.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.