Open AccessA Hybrid Optimization Method for Manufacturing Cell Scheduling with Random Interruptions Based on Improved Wolf Pack Algorithm and Simulation
Author(s) -
Zian Zhao,
Zhou Hong
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2173/1/012075
Subject(s) - mathematical optimization , job shop scheduling , computer science , algorithm , energy consumption , convergence (economics) , scheduling (production processes) , gaussian , engineering , mathematics , economic growth , electrical engineering , economics , schedule , physics , quantum mechanics , operating system
Cell scheduling is an important issue in the cell manufacturing system. Considering the problems of machine interruption and energy consumption, this paper establishes a stochastic optimization model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A hybrid algorithm, based on the wolf pack algorithm (WPA) and simulation, is proposed to solve the problem. In order to deal with the problems of slow convergence speed and easily falling into a local optimum which often happens for the standard WPA, the iterative local search strategy, Cauchy mutation strategy, and Gaussian disturbance are introduced into the search process of WPA to improve its performance. The solution with stochastic parameters is evaluated via simulation. Numerical experiments demonstrate that the proposed hybrid algorithm shows a good performance in both solution quality and convergence speed, and a satisfactory solution to the problem can be reached within a reasonable number of iterations.