Traffic network vulnerability problem bionic optimization method based on myxomycete foraging behaviors

Abstract

The invention discloses a traffic network vulnerability problem bionic optimization method based on myxomycete foraging behaviors. The method comprises the steps of adopting the myxomycete foraging behaviors to simulate and optimize a traffic network vulnerability problem; parallelly solving the traffic network routes in different directions by using a plurality of viscous bodies of a single mucus bacterium; simulating the traffic network nodes into an external food source; simulating a line between two nodes in a traffic network into a viscous deformation body, simulating the traffic network into a myxomycete protoplasm covering all external food sources, simulating the traffic transportation into the transportation of the in-vivo nutrient substances, and simulating the traffic network vulnerability optimization problem into a myxomycete foraging network optimization problem. According to the bionic method, the traffic network vulnerability problem can be efficiently solved in an optimized mode, the social cost is saved, the resource use efficiency is improved, and the problem solving process of the researchers is simplified.

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 solutio

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