This article will be divided into three sections: past, present, and future. The past section will trace major events that created business logistics as it is practiced today. In particular, do the events portend the future of business logistics and supply chain management? The present section will attempt to summarize the state of business logistics. How business logistics relates to supply chain management will be addressed. The future section will make some predictions as to the issues that need to be addressed and the events that will likely take place in the near term. Key wordsLogistics, Supply Chain Management, Logistics history. ResumoEste artigo se divide em três seções: passado, presente e futuro. A sessão sobre o passado traça os eventos mais importantes que criaram a logística empresarial como ela é praticada hoje. Em particular, tais eventos anunciavam o futuro da logística empresarial e do gerenciamento da cadeia de suprimentos? A sessão sobre o presente tenta resumir o estado da logística empresarial. Como a logística empresarial se relaciona com o gerenciamento da cadeia de suprimentos está abordado. A sessão futuro faz algumas previsões acerca das questões que precisam ser discutidas e dos eventos que provavelmente acontecerão em futuro próximo. Palavras-chaveLogística, gerenciamento da cadeia de suprimentos, história da logística.

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In this paper, a stochastic vehicle routing problem is considered. In particular, customer demand is assumed to be uncertain, and actual demand is revealed only upon the visit to the customer. Instead of adopting the simple recourse action of returning to the depot whenever the vehicle runs out of stock, the points along the route at which restocking is to occur are designed into the route. The restocking points may be before a stockout actually occurs. Two heuristic algorithms are developed to construct both single and multiple routes that minimize total travel cost. The computational results show that the heuristic procedures produce quality solutions and are efficient.

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Distribution networks frequently contain multiple locations where product is held as inventory. These may be plants, warehouses, and retail outlets. Traditionally, inventory levels at these locations have been determined by optimizing the cost, demand, and customer service factors local to the particular inventory. With improvements in business information systems, it has become increasingly popular to treat multiple inventory locations as virtual inventories. That is, when customer demand cannot be served from the primary assigned location, other comparable inventory locations, usually more distant, may be used as backup stocking points for serving customer demand. Although delivery cost may be increased, customers actually receive fill rates approaching 100% even when the product in-stock probabilities for the individual stocking points are somewhat lower. While maintaining high fill rates for customers, stocking at low system-wide inventory levels is the appeal of filling customer orders from multiple inventories.In this article, a traditional inventory planning approach is compared with one that is based on filling customer demand from any one of several stocking locations. This provides insights into the impact of inventory control methods, item fill rates, demand dispersion among inventory locations, and relevant inventory costs on system inventory levels. Guidelines are provided for determining the items that should be handled in the traditional manner and those that should be managed as virtual inventories, thus creating a mixed control strategy for the inventoried items. TRADITIONAL INVENTORY PLANNINGCommon pull-type inventory control systems set stocking levels based on demand, costs, and service requirements associated with the defined demand territory of the inventory location. These territories are often determined from location analyses that make demand assignments among multiple facilities. The motivation for this localized control is that it leads to lower inventory levels in a stock location than from alternative control methods such as a push-type method. As shown in Figure 1, all demand is assumed to be served from its primary assigned location. Demand that JOURNAL OF BUSINESS LOGISTICS, Vol.24, No.2, 2003 65 cannot be filled immediately is either backordered or lost. Demand and inventory at other locations play no role in setting the stocking levels at any particular location.Pull-type stocking methods range from EOQ-based to stock-to-demand approaches. The EOQbased methods are commonly known as reorder point, periodic review, min-max, or their variants. On the other hand, stock-to-demand methods set inventory levels in direct proportion to demand. Targeting a certain number-of-weeks supply (inventory turnover) and using a multiple of the forecast are examples of this method.Product availability, or fill rate, is set at less than 100% to avoid excess carrying costs. Depending on the stocking method, product availability is determined statistically or through quantities added to forecasted re...