An urban underground logistics system(ULS)is one important means of solving urban traffic problems that has unique advantages.Freight transportation in China requires a new transportation mode.Therefore,ULS has garner...An urban underground logistics system(ULS)is one important means of solving urban traffic problems that has unique advantages.Freight transportation in China requires a new transportation mode.Therefore,ULS has garnered increasing attention.However,to date,few scholars and practitioners have investigated ULS in China.Although ULS shows good development opportunities,it also faces great challenges.Based on the Macro-environment and situation analysis(PEST-SWOT)model,which is a strategic analysis method that combines both SWOT and PEST to effectively identify advantages,disadvantages,opportunities and threats,this paper first uses PEST to analyze the macro-environment of ULS in China and identify its internal factors(i.e.,advantages and disadvantages)and external factors(i.e.,opportunities and threats).Next,based on the SWOT framework,this paper proposes several development strategies and recommendations that provide a comprehensive and novel perspective to the study of ULS in China.展开更多
Mobility,pollution,and other barriers against sustainable goods movement are pushing local administrators to seek innovations in urban transportation infrastructure.The urban underground logistics system(ULS)has been ...Mobility,pollution,and other barriers against sustainable goods movement are pushing local administrators to seek innovations in urban transportation infrastructure.The urban underground logistics system(ULS)has been recognized as a prospective alternative to realize large-scale automated freight distribution within and around megacities.This paper proposes an integrated approach combing system dynamics and agent-based modeling to evaluate the long-term development and operating status of a city-wide ULS project.The project boundaries regarding underground network expansion,stakeholders’attributes,and social-environmental benefit metrics were structured as eight highly-interacted agent modules.Critical decision variables of agents in terms of supply-demand equilibrium,investment plan,pricing-to-market and willingness-to-pay were incorporated into three formulized subsystem models.From empirical perspective,the urban territory of Beijing,China,was taken as a case to simulate the development footprints of ULS project under different funding options and market acceptance degrees.Results show that ULS has significant competence with respect to service capacity and profitability,while enabling billions of dollars of external cost-saving annually.Moreover,the comprehensive performance of ULS project regarding economic incomes,benefits,market demand,and construction schedule can reach satisfactory trade-offs through adaptively adjusting the funding policies,incentives and pricing portfolios during project development.展开更多
矿井作业环境复杂,各类地质灾害以及水害极易影响井下安全生产,因而预先对灾害发生时的人员逃生路径进行规划很有必要。为获取矿井最短逃生路线,提出了一种改进灰狼优化算法的路径规划方法。该方法针对灰狼优化算法(Grey Wolf Optimizat...矿井作业环境复杂,各类地质灾害以及水害极易影响井下安全生产,因而预先对灾害发生时的人员逃生路径进行规划很有必要。为获取矿井最短逃生路线,提出了一种改进灰狼优化算法的路径规划方法。该方法针对灰狼优化算法(Grey Wolf Optimization,GWO)早熟收敛和易陷入局部最优解的不足,提出了一种基于Logistic映射和Tent映射组合的改进灰狼算法(LT-GWO),提高其全局搜索能力。结合矿井实际工作环境,将改进算法应用于井下逃生路径规划,并通过设定合理路径约束和限制条件,获得了较好的路径规划结果。研究表明:所提算法在平均路径长度、路径长度标准差、平均迭代次数和平均寻优耗时等指标上显著优于已有算法,并且具有较好的鲁棒性。所提算法对于矿井灾害等应急场景下的路径规划问题研究有一定的参考价值。展开更多
1 Introduction Underground logistics systems(ULSs)are a set of self-contained,multimodal,and intelligent physical distribution concepts that enable the automated movement of goods via tunnels and underground pipelines...1 Introduction Underground logistics systems(ULSs)are a set of self-contained,multimodal,and intelligent physical distribution concepts that enable the automated movement of goods via tunnels and underground pipelines installed within and between cities(Visser,2018).ULSs are also recognized as the fifth type of logistics and generic supply system after seaways,airlines,roads,and railways(Qian and Guo,2007).展开更多
基金The work described in this paper is supported by the National Natural Science Foundation of China(NSFC,Project No.71631007).
文摘An urban underground logistics system(ULS)is one important means of solving urban traffic problems that has unique advantages.Freight transportation in China requires a new transportation mode.Therefore,ULS has garnered increasing attention.However,to date,few scholars and practitioners have investigated ULS in China.Although ULS shows good development opportunities,it also faces great challenges.Based on the Macro-environment and situation analysis(PEST-SWOT)model,which is a strategic analysis method that combines both SWOT and PEST to effectively identify advantages,disadvantages,opportunities and threats,this paper first uses PEST to analyze the macro-environment of ULS in China and identify its internal factors(i.e.,advantages and disadvantages)and external factors(i.e.,opportunities and threats).Next,based on the SWOT framework,this paper proposes several development strategies and recommendations that provide a comprehensive and novel perspective to the study of ULS in China.
基金supported bythe National Natural Science Foundationof China(grants No.71631007 and 71971214)。
文摘Mobility,pollution,and other barriers against sustainable goods movement are pushing local administrators to seek innovations in urban transportation infrastructure.The urban underground logistics system(ULS)has been recognized as a prospective alternative to realize large-scale automated freight distribution within and around megacities.This paper proposes an integrated approach combing system dynamics and agent-based modeling to evaluate the long-term development and operating status of a city-wide ULS project.The project boundaries regarding underground network expansion,stakeholders’attributes,and social-environmental benefit metrics were structured as eight highly-interacted agent modules.Critical decision variables of agents in terms of supply-demand equilibrium,investment plan,pricing-to-market and willingness-to-pay were incorporated into three formulized subsystem models.From empirical perspective,the urban territory of Beijing,China,was taken as a case to simulate the development footprints of ULS project under different funding options and market acceptance degrees.Results show that ULS has significant competence with respect to service capacity and profitability,while enabling billions of dollars of external cost-saving annually.Moreover,the comprehensive performance of ULS project regarding economic incomes,benefits,market demand,and construction schedule can reach satisfactory trade-offs through adaptively adjusting the funding policies,incentives and pricing portfolios during project development.
文摘矿井作业环境复杂,各类地质灾害以及水害极易影响井下安全生产,因而预先对灾害发生时的人员逃生路径进行规划很有必要。为获取矿井最短逃生路线,提出了一种改进灰狼优化算法的路径规划方法。该方法针对灰狼优化算法(Grey Wolf Optimization,GWO)早熟收敛和易陷入局部最优解的不足,提出了一种基于Logistic映射和Tent映射组合的改进灰狼算法(LT-GWO),提高其全局搜索能力。结合矿井实际工作环境,将改进算法应用于井下逃生路径规划,并通过设定合理路径约束和限制条件,获得了较好的路径规划结果。研究表明:所提算法在平均路径长度、路径长度标准差、平均迭代次数和平均寻优耗时等指标上显著优于已有算法,并且具有较好的鲁棒性。所提算法对于矿井灾害等应急场景下的路径规划问题研究有一定的参考价值。
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.72271125 and 71971214).
文摘1 Introduction Underground logistics systems(ULSs)are a set of self-contained,multimodal,and intelligent physical distribution concepts that enable the automated movement of goods via tunnels and underground pipelines installed within and between cities(Visser,2018).ULSs are also recognized as the fifth type of logistics and generic supply system after seaways,airlines,roads,and railways(Qian and Guo,2007).
