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KIAM Preprint  39, Moscow, 2024
Authors: Shmyglev D.N., Sudakov V.A.
Reinforcement Learning Model for Enterprise Fleet Optimization
This work highlights the solution to the problem of finding the minimum size of an enterprises vehicle fleet, with which it is possible to solve problems similar to the problem of several traveling salesmen. The proposed approach models a reinforcement learning environment where an agent must drive around given waypoints with multiple vehicles. The conducted computational experiments showed the effectiveness of machine learning models in solving the combinatorial optimization problem.
reinforcement learning, combinatorial optimization, traveling salesman problem, car fleet
Publication language: russian,  pages: 13
Research direction:
Mathematical modelling in actual problems of science and technics
Russian source text:
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About authors:
  • Shmyglev Dmitry Nikolaevich, University under the Government of the RF
  • Sudakov Vladimir Anatolievich, RAS; Financial University under the Government of the RF