Today, maritime transportation has been grown due to decentralized production and increased communication between different countries. Container transportation has contributed a significant share of global transportation due to the possibility of moving a large volume of goods at a reasonable cost. With the expansion of container transportation, container terminals as a place to transport containers between land and sea play a pivotal role in the global transportation network. Container terminals are divided into seaside and landside. In most container terminals, the storage space of the containers and the crossing lines between the yard blocks is predetermined. Increasing container transportation in this fixed space will cause traffic at the terminals and slow down retrieving and loading containers in the yard. One of the main issues at the landside of terminals is the storage space assignment problem, in which the storage location of the containers at the storage area is determined according to the prevailing conditions and the time of their entry into the yard. The yard crane is one of the handling equipment that affects retrieving and loading the containers. One of the problems raised in connection with the yard crane is the yard crane deployment. In the yard crane deployment problem, the number of active yard cranes in each block and the movement of cranes between the blocks of the yard are determined. To better manage the terminals and reduce costs, the main problems at the seaside and the landside need to be addressed in an integrated manner. Literature review shows that despite the importance of the matter, the berth allocation problem, the storage space assignment problem, and the yard crane deployment problem have not been studied in an integrated manner.In this research, an integrated mixed integer programming model has been provided to investigate the storage space assignment problem, the berth allocation problem, and the yard crane deployment with the traffic congestion at the passing lines consideration on the daily planning horizon. The objective function of this mathematical model includes minimizing the yard crane movement cost, the yard crane operating cost, the cost related to the route length of the container transportation between the berth and the yard, and the penalty cost caused by delaying the vessels. In the proposed model, the discrete berth layout has been considered. The movement capacity is determined to prevent traffic congestion in the passing lines. Since the storage space assignment problem and the yard crane deployment problem in an integrated manner and also the berth allocation problem are NP-hard, the combination of these problems does not reduce the total complexity. To solve the stated problem, an accelerated Bendersʹ decomposition algorithm has been proposed. The combinatorial Benders’ cut is used to accelerate the Benders’ decomposition algorithm. Also, 8 valid inequalities based on the concepts and assumptions of the problem are considered to accelerate the Bendersʹ decomposition algorithm. To validate the proposed model, 32 instances are generated based on the data production framework in the literature, and their results are presented. According to the results, the integrated model has a good performance in solving small and medium scale instances. The accelerated Bendersʹ decomposition algorithm has achieved optimal solution in small and medium scale instances in the mean of less time compared to the integrated model. Also, according to the results, this algorithm has a good performance in solving instances on large scale. Different sizes of instances have been designed and solved to eva‎luate the effect of the integration of the problems. According to the results, an average 11.15 percent improvement in costs has been obtained from the integration of the problems related to the non-integration state.

مهدي علينقيان

محمد رئيسي نافچي، فرشته پرورش