Container slot allocation policy in vessel pool alliance under stochastic demand

Abstract

The vessel pool alliance is a prominent cooperation model within the liner shipping industry, where a joint operator manages the collective shipping capacities of all alliance members. The primary challenge for the alliance manager is the efficient allocation of container slots among cargoes with stochastic demand. This study addresses this complex problem by formulating it as a stochastic linear programming model aimed at maximizing the alliance’s total freight revenue while simultaneously ensuring adequate revenue for each member operator, thereby maintaining long-term alliance stability. To solve this problem, we first employ an enhanced Depth-First Search algorithm to identify a set of feasible transportation paths for each cargo. Subsequently, we develop an efficient policy to determine the optimal slot allocation for each realized demand scenario. Numerical experiments using both synthetic and real-world data demonstrate that our proposed policy significantly outperforms the container slot exchange alliance and independent operation modes currently prevalent in practice. Our approach notably enhances revenues for both the alliance as a whole and individual member operators by optimizing the utilization of slot resources.