Optimization method for vehicle path planning of assembly type construction site

Abstract

The invention discloses an optimization method for vehicle path planning of an assembly type construction site. The method comprises the following steps: defining important elements in a fabricated construction site vehicle path optimization problem, setting parameters, and converting two-dimensional coordinates of a construction site into an Euclidean distance matrix; running an ant colony algorithm, performing probability operation of selecting a next access stacking point according to a roulette selection algorithm, and continuously performing pheromone updating; and, according to the genetic algorithm, encoding three important parameters alpha, beta and rho in the ant colony algorithm which are used as dyes, after the optimal combination of alpha, beta and rho is obtained through crossover and mutation operation, taking the optimal combination as an input parameter and then substituting the input parameter into the ant colony operation, and after finite iteration is performed, finally obtaining the optimal path of the vehicle. According to the method, the iterative performance and the optimization efficiency of the model are improved, a local optimal solution is prevented frombeing obtained, and meanwhile, the convergence speed of the model is increased, so that the method is greatly helpful to the scheduling optimization problem of prefabricated part transport vehicles ina prefabricated building site.

Description

technical field [0001] The invention belongs to the cross-technical application fields of construction site management and artificial intelligence technology, information technology and computer technology. It mainly involves a method combining genetic algorithm (GA) and improved ant colony algorithm (ACS) to optimize the vehicle routing problem at the construction site of prefabricated buildings. Background technique [0002] As a new industrial model in the current construction industry, prefabricated buildings have the characteristics of energy saving, low cost, short construction period, high production efficiency and good quality. Since the prefabricated building transfers a large number of on-site operations to the factory, and then transports the parts and components required for the building to the site for effective connection, the prefabricated building construction is more lean and efficient in terms of management than the traditional cast-in-place site. Systemat...

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Problems solved by technology

[0003] The traditional ant colony algorithm has the characteristics of self-organization, self-adaptation, self-learning, parallelization, positive feedback, etc., and can solve complex combinatorial optimization problems, but there are still some disadvantages

The main performance is that it is easy to obtain local optimal solutions, lack of heuristic factors, and cause blind search. These problems will increase the path distance of on-site vehicles, and cannot obtain the best optimal solution. They will also affect the convergence speed of the algorithm and increase the resources of the model. Occupation, etc.

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