Abstract:In this article, we introduce the capacitated warehouse location model with risk pooling (CLMRP), which captures the interdependence between capacity issues and the inventory management at the warehouses. The CLMRP models a logistics system in which a single plant ships one type of product to a set of retailers, each with an uncertain demand. Warehouses serve as the direct intermediary between the plant and the retailers for the shipment of the product and also retain safety stock to provide appropriate service levels to the retailers. The CLMRP minimizes the sum of the fixed facility location, transportation, and inventory carrying costs. The model simultaneously determines warehouse locations, shipment sizes from the plant to the warehouses, the working inventory, and safety stock levels at the warehouses and the assignment of retailers to the warehouses. The costs at each warehouse exhibit initially economies of scale and then an exponential increase due to the capacity limitations. We show that this problem can be formulated as a nonlinear integer program in which the objective function is neither concave nor convex. A Lagrangian relaxation solution algorithm is proposed. The Lagrangian subproblem is also a nonlinear integer program. An efficient algorithm is developed for the linear relaxation of this subproblem. The Lagrangian relaxation algorithm provides near-optimal solutions with reasonable computational requirements for large problem instances.

Many outpatient clinics are experimenting with open access scheduling. Under open access, patients see their physicians within a day or two of making their appointment request, and long-term patient booking is very limited. The hope is that these short appointment lead times will improve patient access and reduce uncertainty in clinic operations by reducing patient no-shows. Practice shows that successful implementation can be strongly influenced by clinic characteristics, indicating that open access policies must be designed to account for local clinical conditions. The effects of four variables on clinic performance are examined: (1) the fraction of patients being served on open access, (2) the scheduling horizon for patients on longer-term appointment scheduling, (3) provider care groups, and (4) overbooking. Discrete event simulation, designed experimentation, and data drawn from an intercity clinic in central Indiana are used to study the effects of these variables on clinic throughput and patient continuity of care. Results show that, if correctly configured, open access can lead to significant improvements in clinic throughput with little sacrifice in continuity of care.

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In this paper we consider a centralized logistics system in which a single company owns the production facility and the set of retailers and establishes warehouses that will replenish the retailers' inventories. We analyze the potential savings that the company will achieve by allowing its retailers to be sourced by more than one warehouse probabilistically, through the use of information technology. We facilitate the discussion on the impact of multisourcing by introducing a capacitated location-inventory model that minimizes the sum of the fixed warehouse location costs, the transportation costs, and the inventory costs. The model is formulated as a nonlinear integer-programming problem that has a cost term that is neither concave nor convex. We propose a Lagrangian relaxation solution algorithm to solve the model and successfully test the algorithm on problems with 88 and 150 retailers. Based on the model properties and the sensitivity analysis results, we conclude that multisourcing becomes a more valuable option as transportation costs increase, i.e., constitute a larger portion of the total logistics cost. In addition, we show that in practice only a small portion of the retailers need to be multisourced to achieve significant cost savings.

Purpose – The growing presence of foods that are labelled “locally/ecologically produced” leads to the question of how many consumers consider the impact of their food purchases. Do they value local/ecologically-produced food sufficiently to drive their purchasing behaviour, even if such foods are more costly? Can consumer segments be identified and, if so, what are their characteristics? This paper aims to focus on these questions. Design/methodology/approach – In an exploratory study, the authors surveyed over 400 students from a public university in California asking them to select between apples based on a combination of price, origin and presence/absence of an ecological indicator. The authors collected information on their shopping attitudes, their affinity for international trade and demographic identifiers. Findings – Evidence is found for three consumer segments: the deep green, the price conscious and switchers. The latter are the most prevalent category across demographic and attitudinal indicators, but with increased age, employment/shopping responsibilities, the preponderance of switchers diminishes and more deep green consumers appear. Deep green consumers tend to be both more information and variety seeking than the price conscious ones. Originality/value – By identifying demographic and other characteristics that are likely to qualify consumers as belonging to a specific segment, marketers of local and ecologically produced foods can better target and influence appropriate consumers.