Yves Dallery

Service capacity pooling in M/G/1 service systems

We study the cost-sharing problem among independent service providers in a service capacity pooling system. The effective improvement of such pooling system can be achieved by reducing the resource idleness in case of congestion. In this paper, we model both the service provider and the cooperative coalition as a single server queue. We attempt to answer the following questions: (i) which coalition strategy should be used; and (ii) which allocation rule should be selected in order to maintain the stability of the coalition? In particular, we consider the service pooling with a fixed service capacity for M/G/1 service systems. The benefit of the pooling system is due to the shortened waiting queue in the overall system. We develop the corresponding cooperative game with transferable utility, and analyze the core allocations. Although it is difficult to express a core allocation explicitly for the game, we prove the non-emptiness of the core. We give a reasonable expression of Equal Profit Method to distribute the cost for our game, and investigate a number of cost allocation rules under three typical situations to evaluate the gain of the service pooling strategy for each service provider. The numerical results show that the cost allocation rule proposed gives a reasonable cost-sharing result considering the contribution of each participant.

Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system

With increasing components’ variety in mixed-model assembly lines, industrials show interest in kitting operations using robots. This paper deals with a hybrid kitting system that consists of a robot and an operator working in series to deliver parts to a Just-In-Time mixed-model assembly line. We develop a mathematical model that optimally assigns stock keeping units to either the robot or the operator so that the cycle time of the overall system is optimised. To test the model, a case study from the automotive sector is presented and a sensitivity analysis is carried out on relevant system parameters.

The news-vendor problem with drop-shipping and resalable returns

Abstract As e-commerce expands, more and more products are offered online to attract internet consumers’ interest. These products are then shipped to consumers’ home by a drop-shipper. Drop-shipping seems to be a good option to sell products in addition to physical stores. Furthermore, both types of products, either sold in store or on Internet can be returned by consumers, with often a higher return ratio for those purchased on Internet. To model these two sales channel and the interactions between them, we consider a News-Vendor (NV) managing both a physical store and an online sale channel that can be fulfilled by a drop-shipping option. We also consider the possibility of reselling products that are returned by consumers during the selling season. The concavity of the expected profit is proven and the optimality condition is obtained. Promising results are obtained from a numerical analysis. In particular, we show that the expected profit can be 14.4% less than the optimal expected profit if the return effect is ignored. Using drop-shipping option can reduce the optimal store inventory by 31.2% and if the NV has no drop-shipping option, the expected profit can be 9% less.

Measurement and Management of Supply Chain Performance: Practices in Today’s Large Companies

Abstract Supply chain can be a powerful source of competitive differentiation for today’s companies. For this purpose, a measurement and management system of supply chain performance is paramount. However, companies often failed in this endeavour. The present article examines this area by means of a benchmarking approach analysing eleven large companies’ performance systems and complemented by two brainstorming workshops. The responses of these companies to this need are categorized to form a framework for addressing this critical topic and as a basis for further research.