a b s t r a c tConcern related to sustainability and greenhouse gases has grown among citizens as well as firms, which are increasingly committing to carbon emission reduction targets. However, firms' emissions come from direct and indirect sources, and from the different stages of their supply chain. Therefore, comprehensive supply chain approaches are essential to ensure the cost-effectiveness of carbon management strategies. These approaches should capture operational and environmental trade-offs arising from the interaction between different supply chain processes such as procurement, manufacturing, transport and inventory management. Considering all these processes, we propose a model for supply chain network design that takes demand uncertainty into account and includes decisions on supply chain responsiveness under different carbon policies: caps on supply chain carbon footprints, caps on market carbon footprints, and carbon taxes. Our model supports the analysis of the effect of different policies on costs and optimal network configuration and allows us to distinguish between different product types: functional or innovative products. With detailed numerical examples, we illustrate the type of analysis and managerial insights that can be derived with our model, which include the assessment of supply chains' potential for carbon abatement, the study of the effect of different carbon policies on supply chain costs and network design, the analysis of the impact of various product characteristics, the test of an alternative profit maximisation model, and the determination of the value of a supply chain carbon tax that should induce specific levels of carbon abatement.

a b s t r a c tWe study the location-inventory problem in three-level supply networks. Our model integrates three decisions: the distribution centers location, flows allocation, and shipment sizes. We propose a nonlinear continuous formulation, including transportation, fixed, handling and holding costs, which decomposes into a closed-form equation and a linear program when the DC flows are fixed. We thus develop an iterative heuristic that estimates the DC flows a priori, solves the linear program, and then improves the DC flow estimations. Extensive numerical experiments show that the approach can design large supply networks both effectively and efficiently, and a case study is discussed.

No abstract

No abstract

In health care system, the operating theatre is recognized as having an important role, notably in terms of generated income and cost. Its management, and in particular its scheduling, is thus a critical activity, and has been the sub ject of many studies. However, the stochasticity of the operating theatre environment is rarely considered while it has considerable effect on the actual working of a surgical unit. In practice, the planners keep a safety margin, let's say 15% of the capacity, in order to absorb the effect of unpredictable events. However, this safety margin is most often chosen sub jectively, from experience. In this paper, our goal is to rationalize this process. We want to give insights to managers in order to deal with the stochasticity of their environment, at a tactical-strategic decision level. For this, we propose an analytical approach that takes account of the stochastic operating times as well as the disruptions caused by emergency arrivals. From our model, various performance measures can be computed: the emergency disruption rate, the waiting time for an emergency, the distribution of the working time, the probability of overtime, the average overtime, etc. In particular, our tool is able to tell how many operations can be scheduled per day in order to keep the overtime limited.

No abstract

No abstract

No abstract