Synchromodal Container Transportation: An Overview of Current Topics and Research Opportunities

Riessen, Bart van; Negenborn, Rudy R.; Dekker, Rommert

doi:10.1007/978-3-319-24264-4_27

Cited by 52 publications

(47 citation statements)

References 21 publications

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“…According to [8] and [9], the core idea of the synchromodal concept is the real-time switching between the transport modes.…”

Section: Synchromodal It Platformmentioning

confidence: 99%

“…Upon close inspection of the missed routes, we found the spread of waypoints to be correct in the large segment of the lane, yet the low number of epochs prevented the algorithm to accurately extract waypoints near the starts, and the ends, hence impacting the score. All tests (1)(2)(3)(4)(5)(6)(7)(8)(9)(10) show that increasing the population size has negligible effect on the overall score, and this parameter is removed from further considerations. With tests 4-9, increasing the number of epochs to 800, and finally to 2000, allowed the algorithm to fit all the waypoints, and correctly identify all the lanes.…”

Section: Simulation With Complete and Incomplete Ais Datamentioning

confidence: 99%

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Maritime pattern extraction and route reconstruction from incomplete AIS data

Dobrkovic

Iacob

Hillegersberg

2018

Int J Data Sci Anal

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Effective barge scheduling in the logistic domain requires advanced information on the availability of the port terminals and the maritime traffic in their vicinity. To enable a long-term prediction of vessel arrival times, we investigate how to use the publicly available automatic identification system (AIS) data to identify maritime patterns and transform them into a directed graph that can be used to estimate the potential trajectories and destination points. To tackle this problem, we use a genetic algorithm (GA) to cluster vessel position data. Then, we show how to enhance the process to allow fast computation of incremental data coming from the sensors, including the importance of adding a quad tree structure for data preprocessing. Focusing on a real case implementation, characterized by partially incomplete and noisy AIS data, we show how the algorithm can handle routes intersecting the regions with missing data and the repercussions this has on the route graph. Finally, postprocessing is explained that handles graph pruning and filtering. We validate the results produced by the GA by comparing resulting patterns with known inland water routes for two Dutch provinces followed by the simulation using synthetic data to highlight the strengths and weaknesses of this approach.

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“…According to [8] and [9], the core idea of the synchromodal concept is the real-time switching between the transport modes.…”

Section: Synchromodal It Platformmentioning

confidence: 99%

Section: Simulation With Complete and Incomplete Ais Datamentioning

confidence: 99%

Maritime pattern extraction and route reconstruction from incomplete AIS data

Dobrkovic

Iacob

Hillegersberg

2018

Int J Data Sci Anal

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“…Top Sector Logistics 2011; SteadieSeifi et al 2014;Behdani et al 2016), aiming for real-time optimal transportation planning in an integrated hinterland transportation system. Synchromodality can only really provide an advantage if the intermodal planning problem is considered in conjunction with the product portfolio offered to customers (Van Riessen et al 2015b). Related to this, some researchers have studied the pricing problem of intermodal inland services.…”

Section: Literature Review 21 Intermodal Networkmentioning

confidence: 99%

The Cargo Fare Class Mix problem for an intermodal corridor: revenue management in synchromodal container transportation

2017

Self Cite

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The intermodal hinterland transportation of maritime containers is under pressure from port authorities and shippers to achieve a more integrated, efficient network operation. Current optimisation methods in literature yield limited results in practice, though, as the transportation product structure limits the flexibility to optimise network logistics. Synchromodality aims to overcome this by a new product structure based on differentiation in price and lead time. Each product is considered as a fare class with a related service level, allowing to target different customer segments and to use revenue management for maximising revenue. However, higher priced fare classes come with tighter planning restrictions and must be carefully balanced with lower priced fare classes to match available capacity and optimise network utilisation. Based on the developments of intermodal networks in North West European, such as the network of European Gateway Services, the Cargo Fare Class Mix problem is proposed. Its purpose is to set limits for each fare class at a tactical level, such that the expected revenue is maximised, considering the available capacity at the operational level. Setting limits at the tactical level is important, as it reflects the necessity of long-term agreements between the transportation provider and its customers. A solution method for an intermodal corridor is proposed, considering a single intermodal connection towards a region with multiple destinations. The main purpose of the article is to show that using a limit on each fare class increases revenue and reliability, thereby outperforming existing fare class mix policies, such as Littlewood.

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“…In such a planning paradigm, decision methods must balance the demand with all available services and intermodal transfers each time new information becomes known [13]. Although research about such methods in synchromodal planning problems is on its infancy, several studies show how existing methods for intermodal transport planning can be extended to such problem settings [17] and how significant gains can be achieved in practice [9,14,17].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Due to the timespace nature of DSND problems, graph theory and mathematical programming approaches are commonly used in this area. However, these approaches have computational limitations for large and complex time-evolving problem instances [16], which are characteristics common to synchromodality [13]. To overcome these limitations, additional designs, such as decomposition algorithms [5], receding horizons [6], and model predictive control [10], are necessary.…”

Section: Literature Reviewmentioning

confidence: 99%

Service and Transfer Selection for Freights in a Synchromodal Network

Rivera¹,

Mes²

2016

Lecture Notes in Computer Science

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We study the planning problem of selecting services and transfers in a synchromodal network to transport freights with different characteristics, over a multi-period horizon. The evolution of the network over time is determined by the decisions made, the schedule of the services, and the new freights that arrive each period. Although freights become known gradually over time, the planner has probabilistic knowledge about their arrival. Using this knowledge, the planner balances current and future costs at each period, with the objective of minimizing the total costs over the entire horizon. To model this stochastic and multi-period tradeoff, we propose a Markov Decision Process (MDP) model. To overcome the computational complexity of solving the MDP, we propose an Approximate Dynamic Programming (ADP) approach. Using different problem settings, we show that our look-ahead approach has significant benefits compared to a benchmark heuristic.

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Synchromodal Container Transportation: An Overview of Current Topics and Research Opportunities

Cited by 52 publications

References 21 publications

Maritime pattern extraction and route reconstruction from incomplete AIS data

Maritime pattern extraction and route reconstruction from incomplete AIS data

The Cargo Fare Class Mix problem for an intermodal corridor: revenue management in synchromodal container transportation

Service and Transfer Selection for Freights in a Synchromodal Network

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