The aim of this study is to propose a new mixed integer linear programming (MILP) model to find the minimum required number of yard cranes, Rubber tyred gantry cranes (RTGCs), for completion the total amount of works at the end of planning horizon. In other word, we find the optimal number of yard cranes in a container terminal which completes the total amount of works. The paper supports the proposed method using a numerical example.

Efficient scheduling and using container equipment have been extensively studied by executive managers and researchers from long time ago. One of the important goals of efficient scheduling is minimization of total waiting time, so that the optimum efficiency can be yield. Here, regarding the benefits of Genetic Algorithm (GA), GA is used to solve the yard crane scheduling problem.

A bi-objective mathematical model is developed to simultaneously consider the quay crane and yard truck scheduling problems at container terminals. Main real-world assumptions, such as quay cranes with non-crossing constraints, quay cranes’ safety margins and precedence constraints are considered in this model. This integrated approach leads to better efficiency and productivity at container terminals. Based on numerical experiments, the proposed mathematical model is effective for solving small-sized instances. Two versions of the simulated annealing algorithm are developed to heuristically solve the large-sized instances. Considering the allocation of trucks as a grouping problem, a grouping version of the simulated annealing algorithm is proposed. Effectiveness of the presented algorithms is compared to the optimal results of the mathematical model on small-sized problems. Moreover, the performances of the proposed algorithms on large-sized instances are compared with each other and the numerical results revealed that the grouping version of simulated annealing algorithm outperformed simulated annealing algorithm. Based on numerical investigations, there is a trade-off between the tasks’ completion time and the cost of utilizing more trucks. Moreover increasing the number of YTs leads to better outcomes than increasing the number of QCs. Besides two-cycle strategy and using dynamic assignment of yard truck to quay cranes leads to faster loading and unloading procedure.

The time that containerships or transportation trucks spend in marine container terminals for loading and unloading their cargo is a real cost scenario which affects, not only the smooth operation of ports, but also affect the overall cost of container trade. The operators of shipping lines and container terminals are required to realize the importance of this issue and the costs associated with dealing long queues of ships and trucks at loading or discharging ports. This paper introduces the concept of the classical Analytical Hierarchy Process (AHP) together with the Fuzzy AHP (FAHP) to help the decision makers in their judgments towards implementing costly loading and discharging facilities at their container terminals. The main objective of this study is to provide a decision-making tool and also to introduce the concept of the Multiple Attribute Decision-Making (MADM) technique by using and comparing both of the AHP and FAHP techniques for solving the problem of selecting the most efficient container yard gantry crane amongst three alternatives including Straddle Carriers (SCs), Rubber Tyred Gantry Cranes (RTGs), and Rail Mounted Gantry Cranes (RMGs) by incorporating the quantitative and the qualitative determining attributes into the problem. Both of the AHP and FAHP analyses in this study have shown that RMG, RTG, and SC systems are the best operational alternatives, respectively.

As more and more container terminals open up all over the world, competition for business is becoming very intense for container terminal operators. They are finding out that even to keep their existing Sea Line customers, they have to make them happy by offering higher quality service. The quality of service they can provide depends on their operating policies and the design of the terminal layout. Existing layouts based on designs prepared a long time ago pose inherent limitations. We summarize some of these problems, and report on newer operating policies and designs which can help improve performance.

According to the figures issued by UNCTAD, containerized trade is forecasted to grow by an average annual rate of 5.32 percent between the years 2003 and 2025. This paper studies yard crane scheduling problem between different blocks for a container terminal. The purpose is to minimize the total travel time of the cranes among the blocks and also, the total delayed workload in each block at different time periods. In other words, the forecasted workload within each planning period, additional crane capacity or insufficient crane capacity for each block, the time when cranes should be deployed and the routes of crane movements, all should be determined in a way that satisfies our objectives. Therefore, the problem is formulated as a mixed integer programming (MIP) model. The block pairs between which yard cranes will be transferred during the various periods, are determined by this model. Afterwards, the model is coded by LINGO which uses branch and bound algorithm for solving. The results determine the yard crane movement sequences among the blocks to achieve minimum total travel time for cranes and minimum total delayed workload in blocks at different periods. The biggest portion of the objective function value, for example, with 13 blocks, eight of which lack carne capacity is related to the total travel time of the cranes within the blocks. It is caused by the slow motion of the yard cranes and their large size. Also, total delayed workload calculated for four problems, decreases over the six time periods until it becomes zero. In other words, yard cranes are deployed in an optimal manner. Also, the results show the efficiency of the developed program.

Port equipment should be designed and selected in a manner to best meet maritime transport customers requirements for loading and discharging of cargo. Hence, evaluation and selection of the proper equipment are of great importance due to their direct involvment in port operation.It is necessary to use a mathematical model enable to use in support systems for making decisions that help managers in evaluation and selection of equipment.Hierachic analysis process is one of the most applicable methods in analysis of complicated issues in decision-making.In this research, a model is designed to help decision makers and evaluators of port equipment vendors in selecting the best equipment using the hierarchic analysis method.

Tower cranes are essential for both vertical and horizontal movement of materials in construction and port operations. Optimizing their placement is crucial for reducing costs and enhancing overall efficiency. This study addresses the optimization of tower crane placement using the recently developed Mouth Brooding Fish (MBF) algorithm. The MBF algorithm is inspired by the life cycle of mouth-brooding fish, employing their behavioral patterns and the survival challenges of their offspring to find optimal solutions. The performance of the MBF algorithm is compared with the Genetic Algorithm (GA), Colliding Bodies Optimization (CBO), and Enhanced Colliding Bodies Optimization (ECBO). The results demonstrate that the MBF algorithm is effective and has potential advantages in tackling complex optimization problems.