Browsing by Author "Akhmetbek Y."
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Item Open Access Stochastic Dynamic Vehicle Routing Problem(Faculty of Engineering and Natural Science, 2024) Akhmetbek Y.The Stochastic Dynamic Vehicle Routing Problem (SDVRP), in which customer demands are dynamic and follow a Poisson distribution, is examined in this study. We provide an SDVRP-specific Reinforcement Learning (RL) algorithm and evaluate it against algorithms for Random Selection, Largest-Demand Selection, and Max-Reachable Selection. We also use a Multi-head Attention architecture into our RL algorithm to better capture complex relationships in the dynamic routing environment. We show, by thorough evaluation, how RL with Multi-head Attention may be used to optimize resource usage and route efficiency, providing useful insights for addressing challenging logistics problems in real-world situations.Item Open Access STOCHASTIC DYNAMIC VEHICLE ROUTING PROBLEM SURVEY(СДУ хабаршысы - 2023, 2023) Akhmetbek Y.; Mustakhov T.Abstract. The present article aims to offer an exhaustive and in-depth investigation of the Stochastic Dynamic Vehicle Routing Problem, which remains a significant challenge in the field of transportation logistics. To achieve this objective, we will undertake a meticulous analysis of the latest cutting-edge techniques and methodologies deployed to tackle this complex optimization problem. Furthermore, we will delve into the intricate and multifaceted stochastic and dynamic constraints that pose formidable obstacles to effective route planning and optimization. Through this survey paper, we seek to provide a comprehensive understanding of the current state-of-the-art approaches and highlight the potential avenues for future research in this critical area of transportation logistics. In addition, we will also analyze the application of advanced reinforcement learning methods and Markov decision processes to solve the problem of stochastic dynamic vehicle routing.