Neuro-PLS: A Generalizable Local Search Framework for Multi-objective Combinatorial Optimization

In this paper, we present a novel neural multi-objective combinatorial optimization framework with generalization ability across problems. The main idea is to integrate the framework of Pareto Local Search (PLS), a well-known problem independent multi-objective heuristic, with the concept of learnin...

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Vydané v:	IEEE transactions on evolutionary computation s. 1
Hlavní autori:	Zhang, Haotian, Shi, Jialong, Sun, Jianyong, Zhang, Qingfu, Xu, Zongben
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	Graph neural networks Heuristic algorithms Iron Learning to Optimize Multi-objective Combinatorial Optimization Neural Networks Optimization Pareto optimization Reinforcement Learning Search problems Sun Symbols Training Vectors
ISSN:	1089-778X, 1941-0026
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