Multiobjective Scheduling for Cooperative Operation of Multiple Gantry Cranes in Railway Area of Container Terminal

Abstract

Railway station plays an important role in improving the operation efficiency of rail-sea intermodal container terminal. The cooperative scheduling of multiple gantry cranes (GCs) can reduce the production and operation cost of railway station. Most studies look into discarding the conflict schemes of GCs, which may obtain excellent scheduling results. These existing conflict-free strategies can not contribute to enhancing the cooperative scheduling performance of multiple GCs. This study integrates container trucks into multiple GCs scheduling environment to eliminate those conflicts, and proposes a mixed-integer programming model considering cooperation between multiple GCs and trucks. The model aims to simultaneously minimize the makespan of the container handling system in station, the total empty travel time of GCs and the total energy consumption of both cranes and trucks. To solve the proposed model, a conflict-free operation strategy for multiple GCs based on hybrid indirect loading and unloading (CFHI) is proposed. CFHI strategy is implemented according to the cooperation between GCs and trucks. An effective multi-objective artificial bee colony algorithm (EMOABC) based on CFHI and fuzzy correlation entropy (FCE) is developed. Within the developed algorithm, an encoding/decoding method based on CFHI is designed to represent and decode the population solutions. The FCE is adopted to evaluate and select the better solutions for next iteration evolution. The effectiveness of the proposed CFHI strategy is verified by comparing it with two popular equipment allocation strategies. Extensive experimental results show that proposed EMOABC is effective to the proposed model. Our findings here have significant implications for the cooperative operation of multiple GCs considering energy consumption in container terminal.