The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Gang Chen - One of the best experts on this subject based on the ideXlab platform.

  • terminal appointment system design by non stationary m t ek c t queueing model and genetic algorithm
    International Journal of Production Economics, 2013
    Co-Authors: Gang Chen, Kannan Govindan, Zhongzhen Yang, Tsanming Choi, Liping Jiang
    Abstract:

    Long truck queue is a common problem at big marine container terminals, where the resources and equipment are usually scheduled to serve ships prior to trucks. To reduce truck queues, some container terminals adopt terminal appointment system (TAS) to manage truck Arrivals. This paper addresses two implementation scenarios of TAS: static TAS (STAS) and dynamic TAS (DTAS). First, a non-stationary M(t)/Ek/c(t) queueing model is used to analyse a terminal gate system, and solved with a new approximation approach. Then, genetic algorithm is applied to optimise the hourly quota of entry appointments in STAS for the derived queueing model. Lastly to relax the assumption of knowing the truckers' preferred Arrival Pattern in STAS, we propose the concept of DTAS, which is much easier to apply and can assist individual trucker in making appointment by providing real-time estimation of waiting time based on existing appointments. Our analysis reveals DTAS can significantly increase the system flexibility.

  • reducing truck emissions at container terminals in a low carbon economy proposal of a queueing based bi objective model for optimizing truck Arrival Pattern
    Transportation Research Part E-logistics and Transportation Review, 2013
    Co-Authors: Gang Chen, Kannan Govindan, Mihalis M Golias
    Abstract:

    This study proposes a methodology to optimize truck Arrival Patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck Arrival Pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck Arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck Arrivals can significantly reduce truck emissions, especially at the gate.

  • Modeling Road Traffic Demand of Container Consolidation in a Chinese Port Terminal
    Journal of Transportation Engineering, 2010
    Co-Authors: Zhongzhen Yang, Gang Chen, Douglas R. Moodie
    Abstract:

    This paper models road traffic demand of container trucks in a Chinese container port. The model is helpful for road planning and traffic management in the port. First, we analyze the attributes of road traffic in the port, to distinguish the differences between port area traffic and surrounding urban area traffic. It is found that port area traffic is generated from vessel operations and fluctuates corresponding to two major factors: operation time schedule and the truck Arrival Pattern within an operation time window. Since the first factor is available from terminal operators, the truck Arrival Pattern is the key for modeling port area traffic demand. Second, we conduct a comprehensive survey to collect truck traffic and vessel operation data, which is used to explore the probability distribution of truck Arrivals during the consolidation periods. Third, we develop a traffic demand model based on the probability distribution with unknown parameters, and modify this model by taking the effects of some external factors into account. At last, we estimate the parameters with the collected data, and the result indicates that this traffic demand model has a high quality of estimation especially for peak traffic times.

Piotr Tryjanowski - One of the best experts on this subject based on the ideXlab platform.

  • changes in the timing and Pattern of Arrival of the white stork ciconia ciconia in western poland
    Journal of Ornithology, 2003
    Co-Authors: Jerzy Ptaszyk, Jakub Z Kosicki, Tim H Sparks, Piotr Tryjanowski
    Abstract:

    Changes in the spring Arrival dates of migrant birds, particularly passerines, have been reported from a range of locations. In this paper we take the opportunity provided by a detailed monitoring scheme to examine several features of the timing and Arrival Pattern of White Storks (Ciconia ciconia) in Poznan province, western Poland during the period 1983–2002. In doing so, we address several criticisms associated with the use of first Arrival dates. We found no evidence of a weekend bias to phenological recording and, unlike in some other species, found no effect of population size on recorded Arrival date. Some aspects of the Arrival Pattern got earlier over time and first Arrival appears to have been about 10 days earlier in the last 20 years than in the previous century. Earlier Arrival was associated with warmer spring weather and with a protracted Arrival period. From our experience with this study, we suggest how the general public can be used to collect high quality phenological data.

  • changes in the timing and Pattern of Arrival of the white stork ciconia ciconia in western poland
    Journal of Ornithology, 2003
    Co-Authors: Jerzy Ptaszyk, Jakub Z Kosicki, Tim H Sparks, Piotr Tryjanowski
    Abstract:

    Changes in the spring Arrival dates of migrant birds, particularly passerines, have been reported from a range of locations. In this paper we take the opportunity provided by a detailed monitoring scheme to examine several features of the timing and Arrival Pattern of White Storks (Ciconia ciconia) in Poznan province, western Poland during the period 1983–2002. In doing so, we address several criticisms associated with the use of first Arrival dates. We found no evidence of a weekend bias to phenological recording and, unlike in some other species, found no effect of population size on recorded Arrival date. Some aspects of the Arrival Pattern got earlier over time and first Arrival appears to have been about 10 days earlier in the last 20 years than in the previous century. Earlier Arrival was associated with warmer spring weather and with a protracted Arrival period. From our experience with this study, we suggest how the general public can be used to collect high quality phenological data.

George F. List - One of the best experts on this subject based on the ideXlab platform.

  • Using time-varying tolls to optimize truck Arrivals at ports
    Transportation Research Part E: Logistics and Transportation Review, 2011
    Co-Authors: Xiao-ming Chen, Xuesong Zhou, George F. List
    Abstract:

    An analytical point-wise stationary approximation model is proposed to analyze time-dependent truck queuing processes with stochastic service time distributions at gates and yards of a port terminal. A convex nonlinear programming model is developed which minimizes the total truck turn time and discomfort due to shifted Arrival times. A two-phase optimization approach is used to first compute a system-optimal truck Arrival Pattern, and then find a desirable Pattern of time-varying tolls that leads to the optimal Arrival Pattern. Numerical experiments are conducted to test the computational efficiency and accuracy of the proposed optimization models.

Mihalis M Golias - One of the best experts on this subject based on the ideXlab platform.

Kannan Govindan - One of the best experts on this subject based on the ideXlab platform.

  • terminal appointment system design by non stationary m t ek c t queueing model and genetic algorithm
    International Journal of Production Economics, 2013
    Co-Authors: Gang Chen, Kannan Govindan, Zhongzhen Yang, Tsanming Choi, Liping Jiang
    Abstract:

    Long truck queue is a common problem at big marine container terminals, where the resources and equipment are usually scheduled to serve ships prior to trucks. To reduce truck queues, some container terminals adopt terminal appointment system (TAS) to manage truck Arrivals. This paper addresses two implementation scenarios of TAS: static TAS (STAS) and dynamic TAS (DTAS). First, a non-stationary M(t)/Ek/c(t) queueing model is used to analyse a terminal gate system, and solved with a new approximation approach. Then, genetic algorithm is applied to optimise the hourly quota of entry appointments in STAS for the derived queueing model. Lastly to relax the assumption of knowing the truckers' preferred Arrival Pattern in STAS, we propose the concept of DTAS, which is much easier to apply and can assist individual trucker in making appointment by providing real-time estimation of waiting time based on existing appointments. Our analysis reveals DTAS can significantly increase the system flexibility.

  • reducing truck emissions at container terminals in a low carbon economy proposal of a queueing based bi objective model for optimizing truck Arrival Pattern
    Transportation Research Part E-logistics and Transportation Review, 2013
    Co-Authors: Gang Chen, Kannan Govindan, Mihalis M Golias
    Abstract:

    This study proposes a methodology to optimize truck Arrival Patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck Arrival Pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck Arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck Arrivals can significantly reduce truck emissions, especially at the gate.