When multiple retailers hold inventory to satisfy random demand, retailer inventory-sharing strategies can potentially reduce the demand-supply mismatch and increase overall supply chain performance. In this paper, we experimentally investigate alternative inventory-sharing strategies in a...

In today's competitive environment, most companies tend to adopt a hybrid manufacturing strategy to provide more reliable services to a wide range of customers. Based on a real-world case study, we investigate a production-inventory-distribution system of a company in a complex supply chain. In...

We present a continuous-time stochastic model of an inventory system with record inaccuracy. In this formulation, demand is modeled by a point process and is observable only when it leads to sales. In addition to demand that can reduce the stock, an unobservable stochastic loss process can also...

We propose a new policy architecture to apply deep reinforcement learning (DRL) with a continuous action representation. This contrasts most current DRL implementations that make use of a discrete action space. The latter are not scalable to large problems. To obtain feasible discrete actions,...

Many of the world's replenishable resources are in decline. Optimal harvests with smooth recruitment is well studied but in recent years, ecologists have concluded that tipping points in recruitment are common. Recruitment with a tipping point has low-fecundity below the tipping point and...

We investigate the pricing timing strategy in the context of trade credit (TC), under which the capital-constrained retailer applies for deferred payments from its supplier. Based on the wholesale price offered by the supplier, the retailer determines the order volume before observing the random...