DOI: 10.5176/2251-3701_2.4.93
Authors: Wanying Shi, Jian Guo
Abstract:
Gasoline and diesel fuel is the lifeblood that keeps our daily life moving forward. Inefficient operation of fuel supply leads to unsatisfactory service, time consuming, as well as low economic benefits. Exploring the optimal timing for gas stations to replenish gasoline and diesel is of importance. We propose to apply infinite-horizon Markov Decision Processes (MDPs) to this dynamic problem. Compared with traditional methods for determining the optimal timing of replenishment, such as IB, EOQ, EB, etc., MDPs are better in accurately modeling the situation which needs sequential decision making under uncertainties. For the MDPs modelling gas station replenishment problem, the rewards for any actions taken in the states (the remaining gasoline and diesel inventory status in the oil tank of the gas station) is to keep the duration for stockout and the tanker trucks’ waiting time as low as possible. The optimal policy is to maximize the rewards. A real world case study was presented and a revised infinite-horizon MDPs model was constructed to optimize the time for replenishment. Managerial insights guiding the actions gas stations should take to optimize their replenishment strategies are gained.
Keywords: MDPs, optimization, petroleum industry
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