Abstract
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.
Highlights
Container terminals are the multimodal transportation hubs of the global supply chain and the buffer pool group for converting transportation modes, which plays an important role in containerization
The logistics generalized computation for container terminals (LGC-CT) at the storage yard takes the operation on quayside and that on landside asynchronously and simultaneously into account, and it leads to the LGC-CT executed by container terminal logistics computing co-processors (CTL-CCP) is highly volatile, scattered, and stochastic even from the cycles of weeks, let alone based on days or hours
There were 25 rubber-tired gantry crane (RTGC) and 71 blocks involved in the LGC-CT for the 25 weeks, which includes 18,727 task records, and the ultimate result was that the accessing, handling, stacking, and switching of 526,480 container box unit (CBU) were realized and completed during the LGC-CT procedure
Summary
Container terminals are the multimodal transportation hubs of the global supply chain and the buffer pool group for converting transportation modes, which plays an important role in containerization. The research methodology of most contributions is the fractional or whole combination of mathematical programming, system simulation, intelligent optimization, and simulation based optimization Those are the classical solutions to the operational research and PSAME in the logistics industry. The PSAME in CTLS have been absent a systematic methodology and engineering solution to be applicable to diverse terminal layouts, handling technologies, device configurations, task loads, and the conditions of collection and distribution. Aiming at this case, the computational logistics were proposed preliminarily by us at the 54th IEEE Conference on Decision and Control (CDC 2015) to provide a new methodology and solution to PSAME of CTLS [13]. It was supposed that the CTL-GCA provides an initial abstraction, automation, and analysis problem-oriented explorations frameworks of PSAME to probe into and improve the operation of container terminals
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