In this paper, an efficient genetic algorithm (GA) is presented to solve an extended storage space allocation problem (SSAP) in a CONTAINER TERMINAL. The SSAP is defined as the temporary allocation of the inbound/outbound CONTAINERs to the storage blocks at each time period with aim of balancing the workload between blocks in order to minimize the storage/retrieval times of CONTAINERs. An extended version of a SSAP proposed in the literature is considered in this paper in which the type of CONTAINER affects on Decision making on the allocation of CONTAINERs to the blocks. In real world cases, there are different types (as well as different sizes) of CONTAINERs consisting of several different goods such as regular, empty and refrigerated CONTAINERs. The extended SSAP is solved by an efficient GA for real-sized instances. Because of existing the several equality constraints in the extended model, the implementation of the GA in order to quick and facilitate achieve to the feasible solutions is one of the outstanding advantages of this paper. The performance of the extended model and proposed GA is verified by a number of numerical examples.

This research aims to evaluate quality services in the Rajaee Port CONTAINER TERMINAL by using SERVQUAL model that is a tool for measuring quality services, identification and for analyzing available gaps between expectations and perceptions services. CONTAINER TERMINAL customers at the port of Rajaee are community statistics in this Research. Judgmental sampling method use for selecting sample. The standard and localized questionnaires with Cronbach,s alpha coefficient in the perceptions section was 0.921 and in expectations section was 0.895 that was distributed among the 150 members of sample, which 102 (68%) questionnaires were available. First for analyze the data, the researcher used of LISREL software to check reliability SERVQUAL model (Size Making Model First and Second term) and then used SPSS software to do T Test pair sample for analyzing significant gap between expectations and perceptions respondents. Results obtained in this study indicated that there is a gap between customer,s expectation services and perceptions services in CONTAINER TERMINAL of Rajaee Port in all five dimension of quality services and from weight point of view. the physical dimension is the most important dimension between all dimensions and after that, reliability, assurance, responsiveness and empathy are also important. In addition, physical dimension have maximum gap and empathy dimension have minimum gap between customers, expectations and perceptions.

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.

The present paper concerns quantitative assessment and measurement of throughput of the Shahid Rajaee CONTAINER TERMINAL. It is developed in particular for Shahid Rajaee port as its CONTAINER operation accounts for 90% of the whole CONTAINER-related operation in the country.Efficiency index of the above mentioned CONTAINER TERMINAL was determined using AHP technique so that the overall TERMINAL efficiency could be identified by determining the gravity (importance coefficient) of each parameter affecting the TERMINAL throughput.

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.