The use of artificial intelligence methods for the optimal design of material and product flow routes
Formulating mathematical models of the traveling salesman task for a fleet of various vehicles. Development of an algorithm for determining the Euler cycle. The use of artificial immune systems in solving exemplary tasks.
Research goal
- Formulating a delivery model with a fleet of various delivery vehicles.
- Formulating a model of waste collection along the streets of housing estates.
The scope of work
The research included two problems: the problem of routing and the problem of the Chinese postman, which are mathematical models for optimizing routes for delivery vehicles, vehicles collecting waste, clearing and removing snow from the streets, and complex loading models.
By the methods of graph theory, the task of routing has been reduced to the traveling salesman problem (TSP). An artificial immune system was used to solve TSP. The considered model takes into account constraints such as time windows, the size of the load and criteria such as minimizing the road, travel time and transport costs.
In the task of the Chinese postman, the graph representing the task was extended to the Euler graph by an artificial immune system. In the Euler graph, the Euler cycle can be determined by the methods of graph theory. This cycle is a solution to the problem of the Chinese postman.
Results
Algorithms were developed to solve both problems using artificial immune systems. Optimal routing is important primarily for lowering transport costs, but also for the sake of environmental protection. The choice of routes for vans in large transport companies is most often based on the intuition of drivers and is not always optimal. The artificial immune system used here as a computational tool is not a strict method, but good enough results can be achieved quickly with it.
