Peter Kelle

Forecasting the returns of reusable containers

Executive Summary A number of organizations sell products in containers that can be reused. Illustrative cases include beverages (in kegs, plastic cartons, etc.) and liquid gases (in cylinders). The time from issue to return of an individual container is usually not known with certainty and there is a chance that the container is never returned (because of loss or irreparable damage). In such a situation, even if the demand pattern is known and level with time, it is still necessary to acquire new containers from time to time. Such an acquisition must be initiated when the inventory level of containers drops too low in relation to the anticipated net demand (demand minus returns) during the replenishment lead time. Thus, it is important to forecast the net demand as well as to obtain an estimate of the accuracy of the forecast. In this paper, four different forecasting procedures, based upon different amounts of information, are developed. The information possibilities include recent issues period by period and recent returns (either individually identified or on an aggregate basis). The methods are compared on a wide range of simulated data, including some cases based on empirical data obtained from industry. Not surprisingly, the use of additional information improves the performance. However, most of the benefit associated with using the costly approach of identifying and tracking the issues and returns of individual containers is achieved by the more practical method of recording only aggregate issues and aggregate returns period by period.

Purchasing Policy of New Containers Considering the Random Returns of Previously Issued Containers

A number of organizations sell products in containers that can be reused. The time from issue to return of an individual container is usually not known with certainty and there is a chance that the container is never returned (because of loss or irrepairable damage). Consequently, even under a level demand pattern new containers must be acquired from time to time. In this paper a purchasing policy of these new containers is determined for a finite time horizon so as to minimize the total purchasing and expected carrying costs under a prescribed service level. The associated stochastic model is reduced to a deterministic, dynamic lot-sizing problem with possible occurrence of negative net demand (demand minus return). A transformation into the usual nonnegative demand case allows us to apply well-known deterministic lot-sizing procedures to obtain the solution.

Partnership and negotiation support by joint optimal ordering/setup policies for JIT

Abstract Several studies have focused on the qualitative aspects of establishing and negotiating buyer–supplier partnerships, including Just-In-Time (JIT) supply, but few quantitative models and investigations are available in this area. We explore the two typical cases: suppliers dominance, with large production lot sizes and shipment sizes and buyers dominance with small, frequent shipments. In each case, we compare the optimal shipment policy of the dominant party to the joint optimal policy. The savings or loss for each party and the total system cost improvements are computed which provide the quantitative support for negotiation, compromise, and compensation. We extend the quantitative results for different JIT scenarios. We assume that the buyers order is delivered in n shipments of size q. The suppliers production lot size can also be an integer multiple of the shipment size, QS=mq, and m can be different from n. Only the cases of m=1 and m=n were examined before. This extension can result in substantial savings. We analyze under which circumstances does the saving warrant the more complex setup policy and in which cases is a simpler policys cost close to optimum.

Safety stock reduction by order splitting

In this article we consider an item for which a continuous review, reorder point, order quantity inventory control system is used. The amount of safety stock required depends upon, among other factors, the average value and variability of the length of the replenishment lead time. One way to reduce these quantities is to split orders among two or more vendors. In this article the random lead times are assumed to have Weibull distributions. This permits the development of analytic expressions for the reduction in the expected value and variability of total demand until the critical first (earliest) delivery received from a vendor. An expression is also obtained for the reorder point that provides a given probability of no stockout prior to the first delivery. Lower bounds are given on the order quantity so as to ensure that the probability of a stockout before any one of the later (second, third, etc.) deliveries is sufficiently small to be considered negligible. The analytic and tabular results can be used to estimate the benefits (reduced carrying costs and/or increased service level) of order splitting.

Stockout risk and order splitting

Abstract The importance of reliable supply is increasing with global sourcing and just-in-time (JIT) production. The transition to JIT purchasing implies single sourcing, which often involves problems with unreliable vendors. If a single, reliable supplier is not available, the order can be split among the vendors until a reliable supplier emerges. We address the problem under which circumstances is single or dual sourcing preferable if the objective of the decision is to minimize the stockout risk. Indifference curves show the delivery characteristics when single sourcing, dual sourcing with an even split, and dual sourcing with optimal split are best. The optimal split rate of dual sourcing is provided in the form of exact formulae and simple approximations. We show that dual sourcing is an appropriate alternative to single sourcing as long as the lead-time uncertainty cannot be decreased. Compared to single sourcing, the optimal split in dual sourcing frequently provides a lower stockout risk if the variability of the lead-time demand is considerable. This property holds even for a second supplier with much worse delivery characteristics, if the order quantity is substantially larger than the expected lead-time demand.

Dual Sourcing Using Capacity Reservation and Spot Market: Optimal Procurement Policy and Heuristic Parameter Determination

This contribution focuses on the cost-effective management of the combined use of two procurement options: the short-term option is given by a spot market with random price, whereas the long-term alternative is characterized by a multi period capacity reservation contract with fixed purchase price and reservation level. A reservation cost, proportional with the reservation level, has to be paid for the option of receiving any amount per period up to the reservation level. A long-term decision has to be made regarding the reserved capacity level, and then it has to be decided – period by period – which quantities to procure from the two sources. Considering the multi-period problem with stochastic demand and spot price, the structure of the optimal combined purchasing policy is derived using stochastic dynamic programming. Exploiting these structural properties, an advanced heuristic is developed to determine the respective policy parameters. This heuristic is compared with two rolling-horizon approaches which use the one-period and two-period optimal solution. A comprehensive numerical study reveals that the approaches based on one-period and two-period solutions have considerable drawbacks, while the advanced heuristic performs very well compared to the optimal solution. Finally, by exploiting our numerical results we give some insights into the system’s behavior under problem parameter variations.

To share or not to share? Examining the factors influencing local agency electronic information sharing

The ability of local government agencies to effectively utilise technologies to share information constitutes a critical element in nationwide efforts to fight terrorism, combat crime, and protect citizen safety. Alarmingly, current practices have neither effectively transferred information that local government agencies need, nor adequately captured and propagated information generated by local authorities. The objective of this study is to understand the factors influencing local agency electronic information sharing. The results of an in-depth case study provide a comprehensive understanding of the technological, agency and environmental factors that promote or inhibit electronic information sharing by local agencies. An extensive set of recommendations is put forth to enable government officials to enhance the success of electronic information sharing initiatives. Moreover, the findings carry several important implications for theory and practice.

Transition to just‐in‐time purchasing

The transition from a traditional purchasing system to a JIT purchasing system can be a slow process or even unattainable, because of unreliable suppliers. The purchaser tries to co‐operate with the vendor, with the goal of receiving smaller, more frequent deliveries, on time, with the quality and quantity required. Often the vendor is ready to co‐operate, but is unable to fulfil these requirements. Provides simple models and methods to aid purchasers in this transition state. Gives simple approximate formulas for the minimum safety stock necessary to ensure the required service level of supply. Considers the case of random delays in shipments, random yield and uncertain demand, which are typical characteristics during the transition period. This safety stock depends on the order quantity and the number of shipments. Provides a simple method to find the order quantity, the number of shipments and safety stock, which minimize the joint total cost of the vendor and purchaser and ensure the required level of supply. Analyzes the savings provided by this method and the sensitivity of the models, in detail.

Economic lot scheduling heuristic for random demands

Abstract An extension to the economic lot scheduling problem is given for a single-machine, multi-product line under random demands. The goal is to find the length of production cycles that minimizes the sum of setup and inventory holding costs per unit of time and satisfies the demand for each product at the required service level. First, the single-product finite replenishment inventory model is extended to the case of random demand. Then, a heuristic procedure uses this extension to determine the production cycles for the multi-product case. Computational results and comparisons with other models are reviewed.

Sulfate reduction in Louisiana marsh soils of varying salinities

Potential sulfate reduction and in situ hydrogen sulfide emission rates for three Louisiana marsh soils of varying salinities (salt, brackish, and freshwater) were used to evaluate the influence of soil physicochemical parameters on sulfur transformations in different seasons (summer, winter, and spring). Solid adsorbent preconcentration and emission flux chambers were used in field experiments to measure hydrogen sulfide emissions. Soil redox potential (Eh) was measured at depths between 5 and 50 cm. Duplicate soil cores were obtained and sectioned for laboratory analysis. The fresh and brackish marsh soils were composed predominantly of organic matter, while the salt marsh soils were composed of predominantly minerals. Fresh marsh soils were generally the most oxidized and salt marsh soils the most reduced. In situ hydrogen sulfide emissions, but not potential sulfate reduction rates, were highest for the brackish marsh. Potential sulfate reduction assays may have overestimated in-situ rates, particularly for the more oxidized fresh marsh. Sulfate turnover times were longer in the salt marsh (approximately 40 days) than in either the fresh or the brackish marshes (3–8 days). Tidal action replenishes sulfate less frequently in the fresh and brackish marshes, thus sulfate depletions are more likely. The lowest potential sulfate reduction rates for all marshes occurred in winter. This was attributed to lower temperature and decreased soil sulfate content.