Optimal strategies for the yard truck scheduling in container terminal with the consideration of container clusters

•A multi-objective mathematical model is developed about container clusters.•Non-loaded traveling distance and the shortest completion time of yard truck are considered.•Fuzzy membership function method and the Pareto optimal solution are introduced.•The problem is analyzed and solved by a heuristic-adaptive genetic algorithm. In container loading and unloading operations, container clusters are more suitable for large-scale operation and coupling scheduling of loading and unloading equipment. Taking a container cluster as a work unit, this study analyzes the multi-vessel large container clusters operation and researches the optimal scheduling strategy of the yard truck. A multi-objective mathematical programming model is developed through the pre-distribution of inbound container clusters and outbound container clusters, where the objectives are to minimize the non-loaded traveling distance and obtain the shortest completion time to finish the loading and unloading of containers in multiple vessels. The modeled problem is analyzed and solved by a heuristic-adaptive genetic algorithm. Fuzzy membership function and Pareto optimal solution are used to transform the multi-objective mathematical model into a single objective. The two methods are compared with results from the multi-objective programming problem of the model proposed. The result from the experimental case proved that the result of the Pareto optimal solution is better than that of the fuzzy membership function with regard to the problems of minimizing the distance of non-loaded traveling and finding the shortest completion time to finish the loading and unloading of containers in multiple vessels.