A branching algorithm to solve binary problem in uncertain environment: an application in machine allocation problem

OPSEARCH ◽  
2019 ◽  
Vol 56 (3) ◽  
pp. 1007-1023
Author(s):  
Sujeet Kumar Singh ◽  
Deepika Rani
Keyword(s):  
Allocation Problem ◽  
Uncertain Environment ◽  
Binary Problem ◽  
Machine Allocation

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

2021 ◽  
Author(s):  
Jin Xie ◽  
Xinyu Li ◽  
Liang GAO
Keyword(s):  
Mathematical Model ◽  
Real World ◽  
Artificial Bee Colony ◽  
Electronic Device ◽  
Testing Machine ◽  
Allocation Problem ◽  
Multi Objective ◽  
Bee Colony ◽  
Machine Allocation ◽  
The Mathematical Model

Abstract 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 areapplied 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.

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