Stochastic Cradle Allocation Problem using SimHeuristics

This article addresses the Stochastic Berth Allocation Problem (SBAP), considering uncertainties in ship arrival and service times. The goal is to minimize the Expected Weighted Total Flow Time to ensure port efficiency. We have developed a sim-heuristic algorithm that integrates Iterated Local Search (ILS) with Monte Carlo Simulation (MCS) to identify robust solutions. Dynamic replication control, using confidence intervals, is employed to balance solution quality and computational cost. Experiments in reference instances demonstrate the superiority of sim-heuristics over deterministic approaches, significantly reducing the objective function in uncertain environments. In addition, a risk analysis via Conditional Value at Risk (CVaR) provides a structured tool to assess the trade-off relationship between operational efficiency and reliability.