Disruption management for truck appointment system at a container terminal: A green initiative

Li, Na; Chen, Gang; Govindan, Kannan; Jin, Zhihong

doi:10.1016/j.trd.2015.12.014

Cited by 91 publications

(90 citation statements)

References 21 publications

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“…Reefer mechanics plug and unplug reefer containers such that due times are met [43]. Li, Na, et al addressed the land-side disruption where truck arrivals deviate from their schedule and proposed a response mechanism that maintains the high resilience ability [44]. Ku and Arthanari proposed a stochastic dynamic programming model to calculate the minimum expected number of shuffles for a pile of containers with a departure time window [45].…”

Section: Coordination Optimization Between Ships and Trainsmentioning

confidence: 99%

Study on Scheme of Outbound Railway Container Organization in Rail-Water Intermodal Transportation

2020

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It has been proven that exploring how to achieve an efficient transportation system is a crucial component of every sustainable transportation study. Rail-water intermodal transportation is recognized as one of the future transportation methods for being efficient, economical and environmentally friendly. To improve the efficiency, reduce transportation costs and maximize the resource utilization of outbound intermodal container transportation, based on the relationship between the container central station and the port station in the actual problems, the organization of railway container transportation was studied. A multi-objective optimization model was established in order to minimize the total cost in the process of transportation, which means maximizing the resource utilization and ensuring it is environmentally friendly. Additionally, an improved genetic algorithm (GA) was developed to solve the model. The calculation results of the model are obtained by the simulation calculation. The comparison with the conventional fixed axis transportation organization method proves that the model and algorithm can reduce costs by up to 24.57%. The result also shows that the container transport organization should be tried to satisfy the direct loading and discharging condition of "train-ship," meanwhile reducing the storage time at the high toll central station. In conclusion, the model and algorithm are feasible and effective. Due to the universality of the model, it can be easily used and generalized in or out of China.Europe advocates that railways should take more transportation volumes, which requires an increase in the service level of the multimodal transport chain and increases the market share of railway transportation in terms of medium-and long-distance freight. Specifically, before the end of 2020, they aim to establish a framework system for the management and payment information system of the EU multimodal transport; before 2030, they will require 30% of road freights to be transferred to rails and waterways, and will reach 50% by 2050 [2]. In 2017, the proportions of rail-sea intermodal transportation were 36% in Duis, 39% in Hamburg and 47% in Bremen.However, the development of multimodal transport is different in China. Although it has been more than ten years of promoting the mode of rail-water transportation in China, due to insufficient transportation capacity of the railway system and other reasons, the implementation of rail-water transportation has been slow.With the continuous advancement of the "Thirteenth Five-Year Plan" and the "Belt and Road" strategy, China has established the notion that lucid waters and lush mountains are invaluable assets and acted with resolve and intensity as never before to strengthen environmental protection. At the same time, an aim of energy consumption per unit of GDP (Gross National Product) falling more than 20% has been set. As the pillar industry of the country, the transportation industry will play a vital role in the process.That's why China is entering a g...

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Section: Coordination Optimization Between Ships and Trainsmentioning

confidence: 99%

Study on Scheme of Outbound Railway Container Organization in Rail-Water Intermodal Transportation

2020

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“…The problem of integrated berth allocation and quay crane assignment was addressed for the trade-off between time saving and energy saving in order to minimize the total departure delay of all vessels and the total handling energy consumption of all vessels by QCs [53]. Li et al [54] addressed the ordinary level of land-side disruption where typically some truck arrivals deviate from their schedule in the appointment system, and they aim to find a response strategy that can maintain high resilience ability of the system in neutralizing the impact of disruptions. Venturini et al [55] introduced a novel mathematical formulation that extended the classical berth allocation problem to cover multiple ports in a shipping network under the assumption of strong cooperation between shipping lines and terminals.…”

Section: Literature Reviewmentioning

confidence: 99%

Container Terminal Logistics Generalized Computing Architecture and Green Initiative Computational Pattern Performance Evaluation

Song

2019

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Container terminals are the typical representatives of complex supply chain logistics hubs with multiple compound attributes and multiple coupling constraints, and their operations are provided with the strong characteristics of dynamicity, nonlinearity, coupling, and complexity (DNCC). From the perspective of computational logistics, we propose the container terminal logistics generalized computing architecture (CTL-GCA) by the migration, integration, and fusion of the abstract hierarchy, design philosophy, execution mechanism, and automatic principles of computer organization, computing architecture, and operating system. The CTL-GCA is supposed to provide the problem-oriented exploration and exploitation elementary frameworks for the abstraction, automation, and analysis of green production at container terminals. The CTL-GCA is intended to construct, evaluate, and improve the solution to planning, scheduling, and decision at container terminals, which all are nondeterministic polynomial hard problems. Subsequently, the logistics generalized computational pattern recognition and performance evaluation of a practical container terminal service case study is launched by the qualitative and quantitative approach from the sustainable perspective of green production. The case study demonstrates the application, utilization, exploitation, and exploration of CTL-GCA preliminarily, and finds the unsustainable patterns of production at the container terminal. From the above, we can draw the following conclusions. For one thing, the CTL-GCA makes a definition of the abstract and automatic running architecture of logistics generalized computation for container terminals (LGC-CT), which provides an original framework for the design and implementation of control and decision mechanism and algorithm. For another, the CTL-GCA can help us to investigate the roots of DNCC thoroughly, and then the CTL-GCA makes for conducting the efficient and sustainable running pattern recognition of LGC-CT. It is supposed to provide a favorable guidance and supplement to define, design, and implement the agile, efficient, sustainable, and robust task scheduling and resource allocation for container terminals by computational logistics whether in the strategy level or the tactical one.

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“…They considered backorders, lost sales, and outsourcing options to generate optimal recovery plans. Other recent works related to developing supply disruption mitigation strategies can be found in Yang et al (2009), Li et al (2010, Shao and Dong (2012), Chung et al (2015), Guo et al (2013), Zhang et al (2013), Hu et al (2013), Yan et al (2014), Pal et al (2014, Ray and Jenamani (2016), Do et al (2016), Faghih-Roohi et al (2015), Mogre and D'Amico (2016), and Li et al (2015). Readers interested in supply disruption management are referred to Snyder et al (2016) and Paul et al (2016aPaul et al ( , 2017.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss

et al. 2017

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Transportation disruption, a common source of business interruptions, can cause significant economic loss to a lean supply chain. This paper studies a lean, two-stage suppliermanufacturer coordinated system where a sudden disruption interrupts the transportation network, creating delivery delays, and product quantity losses. We develop a model to generate a recovery plan after a sudden disruption occurrence, to minimize the negative impacts of the disruption. At the same time, given the computational intensity and problem complexity, three heuristics based on the delivery delay and fractional quantity loss caused by a sudden disruption are developed. We conduct a number of numerical experiments to validate our proposed solution methods, and a scenario-based analysis to test the model and analyse the impact of sudden transportation disruption under three disruption scenarios. The performance of presented heuristics against the Generalized Reduced Gradient method are compared. The results reveal that the proposed heuristics can generate a recovery plan accurately and consistently.

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Disruption management for truck appointment system at a container terminal: A green initiative

Cited by 91 publications

References 21 publications

Study on Scheme of Outbound Railway Container Organization in Rail-Water Intermodal Transportation

Study on Scheme of Outbound Railway Container Organization in Rail-Water Intermodal Transportation

Container Terminal Logistics Generalized Computing Architecture and Green Initiative Computational Pattern Performance Evaluation

Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss

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