Low-bridging electric trolley dispatching method for automatic container terminals and system thereof

Abstract

The invention discloses a low-bridging electric trolley dispatching method for automatic container terminals and a low-bridging electric trolley dispatching system for the automatic container terminals. The dispatching method comprises the steps of: step S1: carrying out data acquisition on position information on a low-bridging electric trolley travel line by a data acquisition module, trimming the collected position information, transmitting the position information to an analysis module by a communication module, and meanwhile receiving a returned low-bridging electric trolley dispatching scheme; and step S2: analyzing the received position information by the analysis module, searching and determining the low-bridging electric trolley dispatching scheme according to the analysis results by an execution module, storing the low-bridging electric trolley dispatching scheme by a storage module, and feeding the low-bridging electric trolley dispatching scheme back to the analysis module by a feedback module. The low-bridging electric trolley dispatching method can clearly and completely describe the selection process of the low-bridging electric trolley in the automatic container terminal operating process, assist the automatic container terminal to enhance the operation management, and enhance the operation efficiency of the terminal.

Description

technical field [0001] The invention relates to a dispatching technology of low-bridge electric trolleys, in particular to a dispatching method and system for low-bridge electric trolleys in an automated container wharf. Background technique [0002] The dispatching of low bridge electric trolleys is the first step in the dispatching of electric trolleys in the three-dimensional transmission system, and it is also the step that has the greatest impact on the subsequent dispatching of lifting trolleys. The rationality of dispatching and distribution strategies will directly affect the loading and unloading efficiency of container terminals. Therefore, is one of the key links. In the actual loading and unloading operation, the selected container of a certain low bridge needs to be operated in the horizontal direction by the electric trolley, and the empty movement of the trolley along the horizontal direction of the low bridge is determined by the difference of the selected el...

AI Technical Summary

Problems solved by technology

Through the research and technical reserves in recent years, the research on the three-dimensional track-type electric trolley has gradually deepened, but there is still a big gap with the research on other automated container terminals. The main problems are: (1) The research is too broad and not specific enough

(2) It cannot meet the real-time operation needs of wharf loading and unloading operations

However, the modeling of object-oriented stochastic Petri nets cannot reflect the data flow in the network, although the Petri net based on state modeling can accurately and conveniently define the control logic of the process. In this case, the data flow is related to the control The flow is completely mixed. When the two are different, the Petri net cannot explicitly express this data flow independent of the control flow, that is to say, it cannot be explicitly expressed in the equipment scheduling process of the automated container terminal. The data flow in the production process is not conducive to real-time control of the terminal production system

In addition, traffic flow is characterized by high nonlinearity, ambiguity and uncertainty, while real-time traffic flow forecasting is more significantly affected by external random disturbances. Therefore, how to overcome nonlinearity, uncertainty and randomness when using traffic flow forecasting The problem of interference needs to be used in combination with other predictive modeling methods. Using it alone cannot solve the problem of integrated scheduling and optimization of equipment in the wharf production process.

Although the above-mentioned various energy consumption model modeling methods have their own advantages, they cannot establish a model that meets the real-time scheduling requirements of the wharf, and the solution methods also have certain limitations in search time

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