Optimization Of Automated Container Terminal Yard Operation Considering Energy Consumption

Automated container terminals have become the main trend of green port development due to their green,efficient,intelligent and safe features.Among them,the container yard,as the core of the construction and upgrading of automated container terminals,has a significant impact on the operational efficiency of the terminals.Therefore,terminal operators promote the operational efficiency of automated container terminals by increasing the upgrading of automated operation equipment and adopting advanced automated yard operation equipment,such as battery powered automated guided vehicles(AGVs)unilateral-cantilever rail-mounted gantry crane(URMGC)and AGV-mate.However,while adopting the new technology it is also necessary to improve the management effectiveness of the terminal,combining the characteristics of the new equipment,such as the URMGC interacting with the AGV under the cantilever,the limited battery capacity of the AGV,the decoupling of the AGV-mate and the role of charging,etc.,to optimize the operational process of the container in order to maximize the advantages brought by the adoption of new operational equipment,and thus reduce the energy consumption of the yard equipment and carbon emissions,and promote the construction of green ports.However,there is currently a lack of optimization for the operation process of new equipment from the perspective of reducing energy consumption,and there is a lack of relevant theoretical research foundation.Therefore,from the perspective of green energy conservation,the dissertation takes the new equipment in the automated container terminal yard as the research object,analyzes the operation process in the new automated yard,and proposes optimization strategies for the core resources and equipment of the yard to reduce energy consumption and carbon emissions of the yard equipment.Firstly,the allocation of storage yard space resources was studied,taking into account the driving energy consumption of AGVs.Secondly,under the premise of given container storage locations,the scheduling problem of AGV was studied,aiming to reduce the carbon emission cost of AGV.Finally,considering the impact of decisions related to container space allocation on the operation of yard equipment,integrated optimization was carried out on the space allocation and equipment scheduling of the yard to minimize the driving energy consumption of yard equipment.The main research contents of this paper are as follows.(1)This dissertation takes the container block equipped with URMGCs as the research object,aiming at the allocation of container storage space,combined with the operation characteristics of AGV that can go deep into the container area,proposes a storage space sharing mode based on centralized hosting strategy.With the objective of minimizing the energy consumption of horizontal transportation of containers,a mixed integer quadratic programming model is established and a flexible segment sharing strategy is designed,and a particle swarm algorithm based on the flexible allocation strategy is proposed to solve the problem.By introducing virtual vessels,the goal that the yard space can be shared among different vessels is achieved,thus optimizing the utilization of yard space resources.Finally,a series of numerical experiments were conducted,and the results showed that the proposed solution method significantly outperformed the solver and genetic algorithm in solving efficiency.Moreover,when the block can be divided into more segments,the yard can handle more containers,but at the same time,the management difficulty will also increase accordingly.In addition,enhancing the operational capacity of URMGC,increasing the number of segments,and the number of URMGC in the container area can effectively reduce horizontal transportation energy consumption,and enhancing the operational capacity of URMGC has a greater impact on reducing transportation energy consumption.(2)This dissertation takes battery-driven AGVs as the research object,and proposes a speed control strategy considering the traffic environment for the scheduling problem of AGVs,taking into account their charging demand during operation and the limited charging capacity of the terminal,and combining the influence of different areas of the terminal on the speed.With the objective of minimizing the carbon emission cost and operational delay cost of AGVs,a mixed integer programming model is developed and an adaptive genetic algorithm based on greedy strategy and simulated annealing strategy is designed to solve the problem.By assigning and ranking the operation tasks and swapping tasks of AGVs,the goal of optimizing the yard operation efficiency and carbon emission is achieved.Finally,a series of numerical experiments were conducted,and the results showed that the proposed solution method significantly outperformed the solver and the genetic algorithm based solution method using single strategy in solving efficiency.Moreover,considering the speed variability of AGVs can more accurately characterize the carbon emission and delay costs of AGVs.In addition,increasing the number of AGV equipment and power exchange robots can to some extent reduce the carbon emission and operation delay costs of horizontal transportation.(3)This dissertation takes the resources and equipment of the terminal yard as the research object,taking into account the impact of container space allocation decisions on equipment scheduling operations,combined with the limited buffering effect and charging effect of AGV-mate,proposes an optimization strategy based on a dual loop strategy for the integrated optimization problem of yard space allocation,AGV scheduling,and yard crane scheduling.With the objective of minimizing the energy consumption of equipment and enhancing the range of AGVs,a mixed integer programming model is developed and an adaptive large-neighborhood search algorithm based on a dual-cycle strategy is designed to solve the problem.Through the balance destroy operator and balance repair operator,the operation allocation of inbound and outbound containers is adjusted to form dual-cycle operations of equipment and optimize the scheduling scheme of yard equipment.Finally,a series of numerical experiments were conducted,and the results showed that the proposed solution method significantly outperformed the solver in solving efficiency.Moreover,reasonable equipment configuration in the yard can provide AGVs with stronger endurance.This dissertation combines the application of new storage yard equipment in automated container terminals to study and analyze the changes in the operation process of the storage yard.Based on the goal of energy conservation and consumption reduction,this dissertation proposes optimization strategies that combine the characteristics of different resource optimization scenarios for the allocation of space resources in the storage yard and the scheduling of AGV and storage yard cranes.The aim is to reduce energy consumption and carbon emissions in the storage yard operation of the terminal.At the same time,the effectiveness and efficiency of the optimization method were verified through numerical experiments of different scales.In summary,this dissertation further establishes and improves the theory and methods of optimizing the operation of automated container terminal yards,providing theoretical research support for current decision-making related to resource allocation and equipment scheduling in automated yards,and also providing guidance for future upgrades and renovations of automated container terminals.