Multi-parking-lot multi-vehicle-model vehicle path planning method

Abstract

The invention discloses a multi-parking-lot multi-vehicle-model vehicle path planning method. The method comprises the following steps: 1) establishing an objective function by taking the lowest totalcost of vehicle distribution as an objective; 2) encoding and redefining an operation mode; 3) initializing a population; 4) calculating the fitness of the artificial fish, and recording the optimalindividual; 5) evaluating each fish, selecting the behavior of each fish at the same time, and selecting the behavior with the highest fitness improvement to execute; 6) calculating the fitness of theobtained new population, and updating the optimal solution in the population; 7) performing annealing search on the optimal solution of the population; 8) ending the primary iteration; 9) judging whether a termination condition is met or not, and if so, executing the step 10; otherwise, returning to execute the step 5, and carrying out a new round of iteration; and 10) decoding the finally recorded optimal individual, calculating the reciprocal of the fitness of the optimal individual, i.e., the value of the target function, and after decoding, taking the client between two same vehicle numbers in the obtained decoding sequence as the distribution route of the vehicle, and outputting an optimal scheme when the unused vehicle does not appear in the decoding sequence.

Description

technical field [0001] The invention relates to a vehicle route planning method for multiple parking lots and multiple vehicle models. Background technique [0002] The vehicle routing problem is widely used in daily life, especially with the continuous development of e-commerce, logistics enterprises have more opportunities and challenges, and the cost of logistics transportation is an important part of the service cost of logistics enterprises. Development has a significant impact. Therefore, formulating a reasonable vehicle scheduling and route plan based on the actual situation can save distribution costs to a large extent. Especially with the continuous increase in logistics volume, a reasonable distribution plan will bring greater benefits , while enhancing the competitiveness of logistics companies. Considering the above factors, it is of great significance to study the solution method of this problem. [0003] With the continuous increase of customer demand and dis...

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Problems solved by technology

[0010] (2) Aiming at the defects of slow solution process and low quality of the solution in the prior art, the present invention embeds the simulated annealing algorithm in the artificial fish swarm algorithm, and ensures that the quality of the solution will not decrease after the annealing search

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