Author

A. Soroka

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Open access Jun 2023

Deep Reinforcement Learning for the Capacitated Pickup and Delivery Problem with Time Windows

Abstract The vehicle routing problem with pickup and delivery is one of the most important problems in the context of global urban population growth. Although these kinds of small-size problems can be solved using various classical approaches, a fast (or real-time) route optimizer under real-world constraints (such as...

A. Soroka, A. Meshcheryakov, S. Gerasimov · Pattern Recognition and Imag... · 10 citations

Mar 2024

Smart Routes: A System for Development and Comparison of Algorithms for Solving Vehicle Routing Problems with Realistic Constraints

The problem of route optimization with realistic constraints is becoming extremely relevant in the face of global urban population growth. While we are aware of approaches that theoretically provide an exact optimal solution, their application becomes challenging as the problem size increases because of exponential com...

A. Soroka, German Mikhelson, A. Mescheryakov et al. · Automation and remote contro... · 0 citations

#machine learning Preprint Aug 2026

JAMPR+/L2D: scalable neural heuristic for constrained vehicle routing problems in dynamic environment

It is shown that the JAMPR+/L2D model, proposed in to solve large CPDPTW problems can be adopted in the case of substantial changes of graph distance matrix, and generalizes well for tasks with simpler constraints (CVRP, VRPTW), for different problem sizes and for moderate changes in distance matrixes.

A. Soroka, A. Meshcheryakov · 0 citations