Bionic optimization method for traffic network vulnerability based on slime mold foraging behavior

Abstract

The present invention is based on the bionic optimization method of the traffic network vulnerability problem based on the foraging behavior of slime mold. The method adopts the foraging behavior of slime mold to perform bionic optimization on the vulnerability problem of the traffic network, and uses multiple slime deformable bodies of a single slime mold to complete different The traffic network route in the direction is solved in parallel, the traffic network node is simulated as an external food source, the line between two nodes in the traffic network is simulated as a viscous deformation body, and the traffic network is simulated as a slime mold covering all external food sources Plastome, simulates transportation as the transportation of nutrients in the body, and simulates the optimization problem of the vulnerability of the transportation network as the optimization problem of the slime mold foraging network. This bionic method can efficiently complete the optimal solution of the vulnerability problem of the traffic network, save social costs, improve the efficiency of resource use, and simplify the problem-solving process for researchers.

Description

technical field [0001] The invention belongs to the field of computer bionics, in particular to a bionic optimization method for traffic network vulnerability problems based on slime mold foraging behavior. Background technique [0002] The transportation network planning and design problem can be naturalized as the classic traveling salesman problem (Traveling Salesman Problem, TSP), which is also translated as the salesman problem and the salesman problem. Merrill M. Flood was the first to use a mathematical model to study the TSP problem. In the 1930s, he solved a school bus route planning problem mathematically for the first time. The problem can be described as, assuming that a traveling salesman wants to visit n cities, the traveling route must traverse each city once, and finally return to the original departure city, the traveling salesman can choose the optimal route of the total route. The traveling salesman problem has been proposed for a hundred years. Scientist...

AI Technical Summary

Problems solved by technology

The traveling salesman problem has been proposed for a hundred years. Scientists at home and abroad tend to accept the traveling salesman problem as an NP-complete problem (NP-Complete or NPC) or NP-hard problem (NP-Hard or NPH). There is no effective algorithm, and It is considered that many instances with many nodes (such as traffic networks) cannot be solved using exact algorithms, only approximate optimization algorithms can be used

Third, the accuracy of solving problems by cultivating slime mold is not high enough. Basically, petri dishes are used as maps and oatmeal particles are used as nodes. The space of the petri dish is limited and the oatmeal is large in size, coupled with the influence of the culture medium, it is obvious that Limits the accuracy of the solution

Fourth, cultivating slime molds also needs to occupy valuable space, time and manpower, supporting complex environmental regulation equipment, nutrition and water supply, growth environment control before the experiment, experimental design, data processing and post-experiment cleanup all require cost and professional operation

[0009] With the wide application of computers and the research of computer bionic algorithms, it is possible to use computer bionic methods based on the foraging behavior of slime molds to solve the vulnerability optimization problem of traffic networks, but so far, there is still no such research in the market and various literatures. Discovery of a biomimetic optimization method for traffic network vulnerability based on slime mold foraging behavior

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