A Multi-stage Stochastic Programming Model of Production Planning Problems with Machine Eligibilities and Sequence-Dependent Setups

• Main Authors: Delvinia, 蘇配史
• Other Authors: Chen, Sheng-I
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/s29g5g

碩士 === 國立交通大學 === 工業工程與管理系所 === 107 === Production planning plays an important role in manufacturing systems. The goals of production planning are to reduce production cost, utilize resources effectively, and achieve optimal production and inventory level while satisfying the product demand that varied over time. Production planning problem is often modeled as a lot-sizing and scheduling problem. The sequence-dependent setup is considered in which a capacity loss occurs depending on the sequence of products to produce. The production planning is often challenged by demand uncertainties that affect the productivity of the manufacturing system. This study focuses on a multi-product and multi-period production planning problem where machine eligibility and demand uncertainty are considered. Three demand patterns of increasing, fluctuating, and decreasing demand are analyzed. Results show that the solution quality of multi-stage stochastic programming model is more robust than the one of the deterministic model. Our findings provide valuable insights for decision makers in the area of manufacturing systems.