Titlebook: Reverse Logistics; Quantitative Models Rommert Dekker,Moritz Fleischmann,Luk N. Wassenhov Book 2004 Springer-Verlag Berlin Heidelberg 2004

消極詞匯

暴露他抗議

Managing Dynamic Product Recovery: An Optimal Control Perspectives to deterministic but time varying environments. These dynamic conditions are present in most practical applications, and in the following we will briefly illustrate this aspect using DaimlerChrysler’s engine recovery operations (see Driesch et al., 1997).

Albumin

Production Planning for Product Recovery Managementroduct recovery will be demonstrated by two case examples, one of them concerning remanufacturing of used products in the field of discrete products’ manufacture, and the other considering rework of by-products in the field of process industries.

handle

Ischemia

Quantitative Models for Reverse Logistics Decision MakingThe purpose of this chapter is to outline the state of affairs of quantitative research in reverse logistics and to explain our contribution. To this end, Section 2.1 locates reverse logistics within the broader context of supply chain management. Section 2.2 characterizes the state of reverse logis

emulsify

GRAVE

Collection and Vehicle Routing Issues in Reverse Logistics reduce activities related to the use of new, extractive resources. It is clear, however, that the extra transportation will diminish the environmental benefits of closing the loop. Likewise, inefficient or ineffective transport activities limit the economic success of reprocessing products.

Ischemic-Stroke

Product and Material Returns: Handling and Warehousing Issues, goods, and products throughout the process of manufacturing, warehousing, consumption, and disposal. The focus is on the methods, mechanical equipments, systems, and related controls used to achieve these functions, usually internal, within the company (see, for example, Tompkins et al., 1996). In

生銹

Lot Sizing Decisions in Product Recovery Managementre just-in-time strategy with zero inventories (see, for example, Silver et al., 1998). A first motive is that of transactions, i.e. the presence of setup costs, setup times, and economies of scale. This results in cycle stocks, the underlying problem of which is lot sizing. This will be addressed i

Coronary