Biological film heuristic DNA genetic algorithm-based railway emergency dispatching optimization method and system

Abstract

The invention discloses a biological film heuristic DNA genetic algorithm-based railway emergency dispatching optimization method and system. The method includes the following steps that: 1, railway network topology information is obtained, a railway emergency dispatching optimization problem is transformed into an objective function for minimizing time for a train to depart from an initial station, pass all goods and material stations and go back to the initial station under a condition that distances between each node in railway network topology and the speed of the train are known, and a train travelling path corresponding to shortest time used by the train is obtained; and 2, the parameters of a biological film heuristic DNA genetic algorithm are initialized, and the termination criterion of the algorithm is set; and 3, the biological film heuristic DNA genetic algorithm is utilized to optimize the train travelling path; and 4, whether the algorithm satisfies the termination criterion is judged, if the algorithm satisfies the termination criterion, the train travelling path outputted in the step 3 is adopted as an optimal solution, otherwise, the method returns to the step 3 for further optimization.

Description

technical field [0001] The invention belongs to the field of railway emergency dispatch optimization, and in particular relates to a method and system for railway emergency dispatch optimization based on biofilm-inspired DNA genetic algorithm. Background technique [0002] At present, time is one of the most important factors in railway emergency dispatching. When faced with sudden accidents, efficient railway emergency dispatching can minimize casualties and property losses. Therefore, the most important issue in railway emergency dispatching is to strive for the train running route corresponding to the shortest dispatching time. In recent years, finding the train running route corresponding to the minimum dispatching time has become a research difficulty and hotspot to solve the optimization problem of railway emergency dispatching. [0003] At present, the main methods for the optimization of railway emergency dispatching are genetic algorithm, ant colony algorithm, part...

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Problems solved by technology

(2) However, the conventional genetic algorithm (SGA) replaces the deterministic mechanism conversion mechanism with a random probability conversion mechanism. Although it has advantages over other traditional methods, SGA still has low search efficiency and local search capabilities. Poor and easy to mature and other disadvantages

Because the algorithm converges quickly, requires few parameters, and can solve complex problems that cannot be solved by traditional optimization algorithms, it is widely used in function optimization, neural network training, and some engineering problems. It is still immature in practical application, and has the same disadvantages as other stochastic optimization algorithms: easy to converge prematurely, easy to fall into local optimum, and poor solution accuracy, etc.

[0004] To sum up, the current optimization algorithm makes the optimization process of railway emergency dispatch prone to instability and may fall into local optimum, which leads to low efficiency and accuracy of the train running path corresponding to the minimum dispatch time in the optimization problem of railway emergency dispatch. poor sex

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