| Dr. Leyuan Shi
"Dept. of Industrial Engineering University of Wisconsin-Madison Email: leyuan@engr.wisc.edu "
|
【主题】A Framework for Supply Chain Optimization
【时间】2003-4-11上午10:00【地点】清华经管学院 北406
【语言】中文/英文
【内容摘要】
Supply chain optimization deals with many issues that span a large spectrum of a firm’s activities, from the strategic, through the tactical to the operational level. The operational level refers to day-to-day decision such as scheduling and routing. The tactical level includes decisions which are typically updated anywhere between once every quarter and once every year. These include purchasing and production decision, inventory policies, and transportation strategies. The strategic level deals with decisions that have a long-lasting effect on the firm such as supply chain network design. Supply chain optimization problems are very difficult tasks. Many contributing factors exist; chief among them is the exponential explosion of alternatives normally leading to NP-hard optimization problems. In the case of stochastic optimization, the situation is further complicated by randomness. We have recently developed a new optimization framework called Nested Partitions (NP). One important feature of the NP method is that it can combine global search and local search (heuristic) procedures in a natural way. It is generic and can be applied to both deterministic and stochastic optimization problems. NP is very effective at exploiting domain-specific knowledge within a structured framework that maintains a “global view” of the solution space. Our experience with large-scale supply chain design problems has demonstrated that NP can produce solutions that are significantly better and faster than those produced in commercial software tools (such as CPLEX).
