A Discrete Multi‑Objective Artificial Bee Colony Algorithm for a Real‑World Electronic Device Testing Machine Allocation Problem

作     者：Jin Xie Xinyu Li Liang Gao Jin Xie;Xinyu Li;Liang Gao

作者机构：State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhan 430074China 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2022年第35卷第6期

页      面：136-150页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080901[工学-物理电子学] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Key R&D Program of China(Grant No.2019YFB1704600) National Natural Science Foundation of China(Grant Nos.51825502,51775216) Program for HUST Academic Frontier Youth Team of China(Grant No.2017QYTD04) 

主　　题：Electronic device Machine allocation Multi-objective optimization Artificial bee colony algorithm 

摘      要：With the continuous development of science and technology,electronic devices have begun to enter all aspects of human life,becoming increasingly closely related to human *** have higher quality requirements for electronic *** device testing has gradually become an irreplaceable engineering process in modern manufacturing enterprises to guarantee the quality of products while preventing inferior products from entering the *** the large output of electronic devices,improving the testing efficiency while reducing the testing cost has become an urgent problem to be *** study investigates the electronic device testing machine allocation problem(EDTMAP),aiming to improve the production of electronic devices and reduce the scheduling distance among testing machines through reasonable machine ***,a mathematical model was formulated for the EDTMAP to maximize both production and the scheduling distance among testing ***,we developed a discrete multi-objective artificial bee colony(DMOABC)algorithm to solve EDTMAP.A crossover operator and local search operator were designed to improve the exploration and exploitation of the algorithm,*** experiments were conducted to evaluate the performance of the proposed *** experimental results demonstrate the superiority of the proposed algorithm compared with the non-dominated sorting genetic algorithm II(NSGA-II)and strength Pareto evolutionary algorithm 2(SPEA2).Finally,the mathematical model and DMOABC algorithm were applied to a real-world factory that tests radio-frequency *** results verify that our method can significantly improve production and reduce the scheduling distance among testing machines.