Multi-resource Constrained JSP Under Uncertainty Based on QPSO Algorithm
Production scheduling problem is one of the most basic, important and difficult theoretical research in a manufacturing system. In the past decades of research, most of them mainly focused on purely deterministic production scheduling problem and handled the real production environment with a large number of constraints, simplifying and assumptions. But with the increasingly fierce market competition, increasingly demanding product diversification, shorter product life cycle and more sophisticated structure of the product make the actual scheduling a large number of uncertainties, the traditional model has become difficult to obtain satisfactory results. This paper makes an analysis on the uncertainties of production scheduling, mainly on uncertain operation time and uncertain delivery time. Fuzzy theory is applied to solve such uncertainties. This paper describes the basic principle of quantum particle swarm optimization algorithm. It remains the model of typical particle swarm optimization and introduces a solving process based on QPSO algorithm. This paper tries to solve the typical uncertain production problem based on QPSO: multi-resource constrained Job-shop scheduling problem. Then it makes construction strategies to solve it. The paper simulates with Visual C. The results show that this algorithm is effective.
quantum particle swarm optimization multi-resource constrained optimization
Fengshan Pan Chunming Ye Jihua Zhou
Business School,University of Shanghai for Science and Technology, Shanghai, China
国际会议
The Institute Industrial Engineera Asian Conference 2011(2011年国际工业工程师协会亚洲会议)
上海
英文
460-465
2011-06-10（万方平台首次上网日期，不代表论文的发表时间）