Fuzzy optimization of storage space allocation in a container terminal

Abstract

A fuzzy optimization model of storage space allocation is proposed, and a rolling-planning method is derived. The model takes the uncertainty of departure time of import containers and arrival time of export containers into account. For each planning horizon, the problem is decomposed into two levels: the first level minimizes the unbalanced workloads among blocks using hybrid intelligence algorithm; based on block workloads allocated in the above level, the second level minimizes the number of blocks to which the same group of import containers are split. Numerical results show that the model reduces workload imbalance, and speeds up the vessel loading and discharging process.