Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Tong Xialiang"'
Autor:
Liu, Fei, Yao, Yiming, Guo, Ping, Yang, Zhiyuan, Zhao, Zhe, Lin, Xi, Tong, Xialiang, Yuan, Mingxuan, Lu, Zhichao, Wang, Zhenkun, Zhang, Qingfu
Algorithm Design (AD) is crucial for effective problem-solving across various domains. The advent of Large Language Models (LLMs) has notably enhanced the automation and innovation within this field, offering new perspectives and promising solutions.
Externí odkaz:
http://arxiv.org/abs/2410.14716
The min-max vehicle routing problem (min-max VRP) traverses all given customers by assigning several routes and aims to minimize the length of the longest route. Recently, reinforcement learning (RL)-based sequential planning methods have exhibited a
Externí odkaz:
http://arxiv.org/abs/2405.17272
Autor:
Liu, Fei, Lin, Xi, Liao, Weiduo, Wang, Zhenkun, Zhang, Qingfu, Tong, Xialiang, Yuan, Mingxuan
Neural combinatorial optimization (NCO) is a promising learning-based approach to solving various vehicle routing problems without much manual algorithm design. However, the current NCO methods mainly focus on the in-distribution performance, while t
Externí odkaz:
http://arxiv.org/abs/2405.12262
The neural combinatorial optimization (NCO) approach has shown great potential for solving routing problems without the requirement of expert knowledge. However, existing constructive NCO methods cannot directly solve large-scale instances, which sig
Externí odkaz:
http://arxiv.org/abs/2405.01906
The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design. However, existing methods struggle with large-scale problems, hinderi
Externí odkaz:
http://arxiv.org/abs/2403.19561
Vehicle routing problems (VRPs), which can be found in numerous real-world applications, have been an important research topic for several decades. Recently, the neural combinatorial optimization (NCO) approach that leverages a learning-based model t
Externí odkaz:
http://arxiv.org/abs/2402.16891
Autor:
Liu, Fei, Tong, Xialiang, Yuan, Mingxuan, Lin, Xi, Luo, Fu, Wang, Zhenkun, Lu, Zhichao, Zhang, Qingfu
Heuristics are widely used for dealing with complex search and optimization problems. However, manual design of heuristics can be often very labour extensive and requires rich working experience and knowledge. This paper proposes Evolution of Heurist
Externí odkaz:
http://arxiv.org/abs/2401.02051
Multiobjective evolutionary algorithms (MOEAs) are major methods for solving multiobjective optimization problems (MOPs). Many MOEAs have been proposed in the past decades, of which the search operators need a carefully handcrafted design with domain
Externí odkaz:
http://arxiv.org/abs/2310.12541
Vehicle routing is a well-known optimization research topic with significant practical importance. Among different approaches to solving vehicle routing, heuristics can produce a satisfactory solution at a reasonable computational cost. Consequently,
Externí odkaz:
http://arxiv.org/abs/2303.04147
The bin packing problem exists widely in real logistic scenarios (e.g., packing pipeline, express delivery), with its goal to improve the packing efficiency and reduce the transportation cost. In this NP-hard combinatorial optimization problem, the p
Externí odkaz:
http://arxiv.org/abs/2202.12466