Joint Scheduling Optimization Of Berths And Quay Cranes At Container Terminals Based On Improved Bat Algorithm

Economic globalization has promoted the rapid development of container shipping,and increased competition among container terminals.As the important resources and equipment of the container terminals,how to utilize berths and quay cranes reasonably and shorten ship’s time in ports plays a significant role in improving the efficiency of port loading or unloading,and enhancing the comprehensive competitiveness of ports.This paper mainly focuses on the joint scheduling of berths and quay cranes.Firstly,on the basis of the literature review at home and abroad of the relevant scheduling problems,two kinds of mathematical models of joint scheduling of discrete berths and continuous berths with quay cranes are established for the purpose of minimizing ship’s time in ports.In these models,practical constraints are considered such as the inability to cross the quay cranes and the waiting time caused by the interference of quay cranes.Secondly,a novel bat algorithm is adopted to solve above joint scheduling optimization problems of berths and quay cranes.An improved parallel bat algorithm(IPBA)is proposed to overcome the defects of the bat algorithm,such as premature convergence,slow convergence speed and low optimization accuracy.The main improvement measures are as follows.Firstly,a chaotic initialization method based on the immune concentration concept is proposed.By the way,the individuals with better fitness and lower concentration are selected to form the initial population,which can resist premature convergence and improve convergence speed.Secondly,parallel strategy is introduced to divide the population into two subpopulations of exploration and exploitation,which adopts different inertia weights and stagnate variation strategies to evolve.Regular exchange of information between subpopulations can give full play to the advantages of parallel strategy,and improve the overall performance of proposed algorithm.In order to be suitable for solving scheduling problem,the relevant operations of IPBA are discretized,so that the proposed IPBA can be utilized to solve the continuous,discrete and mixed variable optimization problems.Moreover,IPBA is used to solve the classical function optimization and travelling salesman problems,and comparison and analysis of the optimal results verified the feasibility and effectiveness of proposed IPBA.Finally,IPBA is applied to solve the joint scheduling optimization problems of berths and quay cranes.Based on above established mathematical models and the proposed algorithm,the individual coding,the initial population generation scheme and the realization of related operations are designed respectively.Then,the different scale examples of the two types of models are solved separately.The results show that the optimized scheduling schemes by the proposed algorithm can effectively shorten ship’s time in ports under the corresponding constraints.Consequently,it is verified that the proposed IPBA has better performance in solving the joint scheduling optimization problems of berths and quay cranes.This work provides reference and support for the exploration of relevant optimization algorithm and engineering application,as well as the better solution of the joint scheduling optimization problems of berths and quay cranes.