Using a Hybrid Model on Joint Scheduling of Berths and Quay Cranes—From a Sustainable Perspective

Aijun Liu,Hui Lu,Jiangtao Wang,Haiyang Liu,Xiao Zhang,Sang-Bing Tsai

doi:10.3390/su10061959

Abstract

In response to the problem of the unfair distribution of berths and quay cranes, as well as the optimization of the traffic path in port scheduling, a berth-crane joint scheduling model is proposed. Firstly, a ship is coded according to its geographical location and its arrival time in the form 0, 1. Then, the shortest port time, the minimum system cost, and the minimum unfairness are taken into account with the status quo of the port. Thus, a multi-objective joint scheduling model is established and solved by an improved NSGA-II algorithm. Finally, a practical example is given to verify the validity of the proposed method, the stable and the convergent of the proposed method are proved by many times computer simulations. The novelty of this paper is that we have taken psychological factors of fairness as well as social factors of sustainable development into consideration, and proposed an improved NSGA-II algorithm with random repair operator and self-adaptive operator to solve the multi-objective decision problem on joint scheduling of berths and quay crane.

Highlights

With the acceleration of economic globalization, the marine transport industry is growing rapidly
Han et al [2] considered the rational utilization of resources and the sustainable development of port operation and management, and proposed a multi-objective optimization model to minimize the consumption of resources and the minimum moving distance of the shore bridge
To minimize ship loading and unloading times, Al-Dhaheri et al [23] considered the transit times between the terminals and the yards during the entire container loading and unloading process, proposed a stochastic mixed integer programming model for the Quay Cranes Scheduling Problem (QCSP), and established a container scheduling simulation model that was based on a genetic algorithm to reveal the dynamics and uncertainty

Summary

Introduction

With the acceleration of economic globalization, the marine transport industry is growing rapidly. From the perspective of environmental sustainability, Hu et al [3] established a nonlinear multi-objective mixed integer programming model, which considered the fuel consumption and the emission of ships, and analyzed the effects of the wharf cranes number on the port operation cost, the fuel consumption of ships, and the emission of pollution gas. To minimize ship loading and unloading times, Al-Dhaheri et al [23] considered the transit times between the terminals and the yards during the entire container loading and unloading process, proposed a stochastic mixed integer programming model for the Quay Cranes Scheduling Problem (QCSP), and established a container scheduling simulation model that was based on a genetic algorithm to reveal the dynamics and uncertainty. Research on scheduling optimization models and algorithms is the basis of the study of the problem of berth scheSduustaliinnagbi,litwy 2h0i1c8h, 10h, a19s59stimulated the interest of many scholars

Literature Review

Construction of Joint Scheduling Model of the Port and Quay Cranes

Algorithm Flow and Steps for Problem-Solving

Case Study

Conclusions