No abstract

Localising facilities and assigning product flows in a reverse logistics environment is a crucial but difficult strategic management decision, certainly when value decay plays an important part. Despite numerous publications regarding closed-loop supply chain design, very few addressed the impact of lead times and the high level of uncertainty in reverse processes. In this paper, a single product reverse logistics network design problem with multiple layers and multiple routings is considered. To this end, a new advanced strategic planning model with integrated queueing relationships is built that explicitly takes into account stochastic delays due to various processes like collection, production and transportation, as well as disturbances due to various sources of variability like uncertain supply, uncertain process times, unknown quality, breakdowns, etc. Their impact is measured by transforming these delays into work-in-process, which affects profit through inventory costs. This innovative modeling approach is difficult to solve because of both combinatorial and nonlinear continuous relationships. The differential evolution algorithm with an enhanced constraint handling method is proposed as an appropriate heuristic to solve this model close to optimality. A number of scenarios for a realistic case illustrate the power of this optimization tool.

No abstract

Comprehensive long term maintenance contracts are a recent trend in equipment industries. At the same time increasing environmental concerns and high prices for raw materials stress the importance of remanufacturing activities. Hence, maintenance contracts often result in remanufacturing of some critical components. We consider the situation in which an industrial equipment manufacturer offers multi-year maintenance contracts with an uptime guarantee. To provide these service contracts profitably, the company needs to decide on the contract design: selling price, overhaul interval and uptime guarantee. Moreover, the company has to invest in the required logistics network. The logistics network is determined by the locations, number and capacity level of the remanufacturing facilities and the number of field technicians in each service region. The network design and the overhaul interval affect the level of service in terms of machine uptime, and consequently, the price that customers are willing to pay for the service contract. The lead times throughout the network are stochastic in nature