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

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