In the inventory routing problem, the supplier acts as a central decision maker who determines the replenishment quantities and also, the delivery times and routes to all retailers. In “Inventory Routing Problem Under Uncertainty”, Cui et al. develop a novel framework for the uncertain inventory routing problem and allow ambiguity in the probability distribution of each retailer's uncertain demand. Adopting a service-level viewpoint, they minimize the risk of uncertain inventory levels violating a prespecified acceptable range. They quantify that risk using a new decision criterion, the service violation index, that accounts for how often and how severely the inventory requirement is violated. The solutions proposed here are adaptive in the sense that they vary with the realization of uncertain demand. They provide algorithms to solve the problem exactly and then, demonstrate the superiority of their solutions by comparing them with several benchmarks.

With a rigid requirement for environment protection, governments need to make appropriate policies to induce firms to adopt green technology in consideration of the rapidly increasing demand for environmentally friendly products. We investigated the government policy from the perspective of a supply chain, which consisted of the upstream government (she) and the downstream manufacturing firm (he). The government decided on the policy (tax or subsidy) to maximize the social welfare, while the firm decided on the greenness level of the product, which affects the consumers’ choice behavior and hence his own demand. Assuming else being equal, the government should adopt the tax policy if consumers are very sensitive to the greenness, the cost of greening is high, or the negative impact due to carbon emission is large, and subsidize the firm otherwise. We also conduct some numerical studies when price is endogenous. The main insights can be carried over.