Computational Logistics for Container Terminal Logistics Hubs Based on Computational Lens and Computing Principles

The volatile global shipping market puts forward the higher requirements to the container terminal logistics systems (CTLS) than ever, especially in terms of programming, planning, scheduling and decision. The computational logistics provide a systematic methodology to overcome the issues that differs from traditional approaches distinctly. This paper discusses the theoretical framework, important components and core concept of computational logistics, and then presents the container terminal logistics generalized computation design, implement, execution, analysis and evaluation hierarchy (LGC-DIE-AEH) by the integration of the computational lens and computing principles to explore the computational logistics in the field of CTLS. Subsequently, the execution performance of a quay crane farm at a regional container hub terminal in China is analyzed and evaluated by LGC-DIE-AEH. The crane performance evaluation core indicator framework (CPE-CIF) is proposed by the fusion of the design philosophy and underlying principles of computing architecture, operating system, and virtual machine by computational lens. The CPE-CIF help us to find out the advantages, disadvantages and improvement directions of quay crane farm operation. That illustrates and verifies the feasibility and credibility of LGC-DIE-AEH from the perspective of the practice of container terminal decision-making support at the tactical level.

[1]  Vasant Honavar,et al.  Accelerating Science: A Computing Research Agenda , 2016, ArXiv.

[2]  Peter J. Denning,et al.  Computational Thinking , 2019 .

[3]  Qiang Meng,et al.  Container liner fleet deployment: A systematic overview , 2017 .

[4]  Peter J. Denning,et al.  Computing is a natural science , 2007, CACM.

[5]  Teodor Gabriel Crainic,et al.  Simulation of intermodal freight transportation systems: a taxonomy , 2017, Eur. J. Oper. Res..

[6]  Qingcheng Zeng,et al.  Toward a taxonomy of container terminals’ practices and performance: A contingency and configuration study , 2019, Transportation Research Part A: Policy and Practice.

[7]  Erwin Pesch,et al.  Approaches to empty container repositioning problems in the context of Eurasian intermodal transportation , 2019, Omega.

[8]  Peter J. Denning,et al.  Is computer science science? , 2005, CACM.

[9]  Ahmed El Hilali Alaoui,et al.  Robust optimisation of the intermodal freight transport problem: Modeling and solving with an efficient hybrid approach , 2019, J. Comput. Sci..

[10]  Zhiwei Xu,et al.  High-performance computing environment: a review of twenty years of experiments in China , 2016 .

[11]  Zhi-Wei Xu,et al.  Three New Concepts of Future Computer Science , 2011, Journal of Computer Science and Technology.

[12]  Yuqing He,et al.  Container Terminal Oriented Logistics Generalized Computational Complexity , 2019, IEEE Access.

[13]  Richard M. Karp,et al.  Understanding Science Through the Computational Lens , 2011, Journal of Computer Science and Technology.

[14]  Qiang Meng,et al.  Liner container assignment model with transit-time-sensitive container shipment demand and its applications , 2016 .

[15]  Eitan M. Gurari,et al.  Introduction to the theory of computation , 1989 .

[16]  Jeannette M. Wing.  An introduction to computer science for non-majors using principles of computation , 2007, SIGCSE.

[17]  Jasmine Siu Lee Lam,et al.  A review of energy efficiency in ports: Operational strategies, technologies and energy management systems , 2019, Renewable and Sustainable Energy Reviews.

[18]  Zhiwei Xu,et al.  Computing for the masses , 2011, Commun. ACM.

[19]  Peter J. Denning,et al.  Remaining trouble spots with computational thinking , 2017, Commun. ACM.

[20]  Peter J. Denning,et al.  The profession of ITComputing: the fourth great domain of science , 2009, CACM.

[21]  Peter J. Denning,et al.  Great principles of computing , 2015, CACM.

[22]  Ren Moses,et al.  Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms , 2017, IEEE Access.

[23]  Bin Li.  Container terminal logistics scheduling and decision-making within the conceptual framework of computational thinking , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[24]  Richard M. Karp,et al.  Computer Science as a Lens on the Sciences: The Example of Computational Molecular Biology , 2007, 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007).

[25]  Dong-Ping Song,et al.  Ocean container transport in global supply chains: Overview and research opportunities , 2017 .