Negotiating truck arrival times among trucking companies and a container terminal

Author(s):  
Mai-Ha Phan ◽  
Kap Hwan Kim
Author(s):  
Fakhri Ihsan Ramadhan ◽  
Meditya Wasesa

Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times.


Author(s):  
AGOSTINO BRUZZONE ◽  
FRANCESCO LONGO ◽  
LETIZIA NICOLETTI ◽  
ELEONORA BOTTANI ◽  
ROBERTO MONTANARI

The freight logistics includes all the processes needed to supply industry, retailers and wholesalers and final customers with goods. Such processes generate a flow of goods that, in the global supply chain, mainly relies on the activities carried out within worldwide container terminals. In this paper, the authors present a simulation model of a real container terminal. After some preliminary analyses, the simulation model is first used with Design of Experiments and Analysis of Variance to investigate the effects of different resources allocations (i.e., number of forklifts and tractors) and some parameters (i.e., inter-arrival times, container unloading time) on the container terminal performances in terms of total number of handled containers per day. Then, based on the results achieved through the Design of Experiments and Analysis of Variance, the simulation model is used with genetic algorithms to carry out a range allocation optimization on berth assignment to incoming ships and number of tractors serving each quay crane. The aim of the optimization is the minimization of the average time spent by each ship in the port area (decreasing, as consequence, costs and increasing service level provided to final customers).


2011 ◽  
Vol 13 (2) ◽  
pp. 142-173 ◽  
Author(s):  
Gianfranco Fancello ◽  
Claudia Pani ◽  
Marco Pisano ◽  
Patrizia Serra ◽  
Paola Zuddas ◽  
...  

2005 ◽  
Vol 156 (6) ◽  
pp. 207-210 ◽  
Author(s):  
Claudio Defila

Numerous publications are devoted to plant phenological trends of all trees, shrubs and herbs. In this work we focus on trees of the forest. We take into account the spring season (leaf and needle development) as well as the autumn (colour turning and shedding of leaves) for larch, spruce and beech, and,owing to the lack of further autumn phases, the horse chestnut. The proportion of significant trends is variable, depending on the phenological phase. The strongest trend to early arrival in spring was measured for needles of the larch for the period between 1951 and 2000 with over 20 days. The leaves of the horse chestnut show the earliest trend to turn colour in autumn. Beech leaves have also changed colour somewhat earlier over the past 50 years. The trend for shedding leaves, on the other hand, is slightly later. Regional differences were examined for the growth of needles in the larch where the weakest trends towards early growth are found in Canton Jura and the strongest on the southern side of the Alps. The warming of the climate strongly influences phenological arrival times. Trees in the forest react to this to in a similar way to other plants that have been observed (other trees, shrubs and herbs).


2014 ◽  
Author(s):  
Emmanuel Skarsoulis ◽  
Bruce Cornuelle ◽  
Matthew Dzieciuch
Keyword(s):  

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