ارايه ي ك مدل زمان بندي جرثقيل محوطه در ترمينالهاي كانتينري

Developing a Yard Crane Scheduling Model for a Container Terminal

امروزه تجارت جهاني در بخش حمل و نقل كانتينري رشد و پيشرفت عظيمي داشته است. در اين مقاله، مساله زما نبندي جرثقيلهاي محوطه بين بلوكهاي مختلف در يك ترمينال كانتينري مورد مطالعه قرار م يگيرد. اهداف اين مطالعه، كمينه كردن مدت زمان جابجايي جرثقيلهاي محوطه در بين بلوكها و حجم كاري باقي مانده در بلوكها در دور ههاي زماني مختلف است. بنابراين، در اين پژوهش، مساله زما نبندي جرثقيل محوطه به صورت برنامه ريزي عدد صحيح مختلط ) MIP ( فرموله مي شود. اين مدل مي تواند جفت بلوكهايي را كه جرثقيلهاي محوطه در هر دور ه زماني بين آنها جابجا مي شوند، تعيين كند. سپس مدل در نرم افزار لينگو كدنويسي شده و با استفاده از روش شاخه و كران حل مي شود. نتايج محاسباتي حاصل از حل مدل، توالي جابجايي جرثقيلها در هر دوره بين بلوكها را تعيين مي كند، به طوري كه كمينه زمان جابجايي براي جرثقيلهاي محوطه و كمينه حجم كاري در هر دوره زماني در هر بلوك به دست آيد. همچنين نتايج حاصله نشانگر آن است كه الگوريتم توسعه داده شده از كارآيي لازم برخوردار است.

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.