Imagen de Portada

UCPO: A Universal Constrained Combinatorial Optimization Method via Preference Optimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Fang, Zhanhong, Wang, Debing, Chen, Jinbiao, Wang, Jiahai, Zhang, Zizhen
Formato:	Preprint
Publicado:	2025
Materias:	Neural and Evolutionary Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Detection Region Method-Based Evolutionary Algorithm for Binary Constrained Multiobjective Optimization
por: Huang, Weixiong, et al.
Publicado: (2024)

Multiple-gain Estimation for Running Time of Evolutionary Combinatorial Optimization
por: Huang, Min, et al.
Publicado: (2025)

A Fitness-assignment Method for Evolutionary Constrained Multi-objective Optimization
por: Ajani, Oladayo S., et al.
Publicado: (2023)

Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization
por: Wang, Zeyi, et al.
Publicado: (2024)

Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
por: Qiu, Junhao, et al.
Publicado: (2026)

Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence Model
por: Huang, Jiaxiang, et al.
Publicado: (2024)

Variable Search Stepsize for Randomized Local Search in Multi-Objective Combinatorial Optimization
por: Ren, Xuepeng, et al.
Publicado: (2026)

BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization
por: Liao, Zijun, et al.
Publicado: (2025)

Multidomain Evolutionary Optimization on Combinatorial Problems in Complex Networks
por: Zhao, Jie, et al.
Publicado: (2024)

Generalizing and Unifying Gray-box Combinatorial Optimization Operators
por: Chicano, Francisco, et al.
Publicado: (2024)

Fully Tensorized GPU-accelerated Multi-population Evolutionary Algorithm for Constrained Multiobjective Optimization Problems
por: Huang, Weixiong, et al.
Publicado: (2025)

Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language Models
por: Wu, Xuan, et al.
Publicado: (2025)

Running-time Analysis of ($μ+λ$) Evolutionary Combinatorial Optimization Based on Multiple-gain Estimation
por: Huang, Min, et al.
Publicado: (2025)

A Novel Population Initialization Method via Adaptive Experience Transfer for General-Purpose Binary Evolutionary Optimization
por: Wang, Zhiyuan, et al.
Publicado: (2025)

Decoupling Constraint from Two Direction in Evolutionary Constrained Multi-objective Optimization
por: Sun, Ruiqing, et al.
Publicado: (2025)

Exploration-Exploitation-Evaluation (EEE): A Framework for Metaheuristic Algorithms in Combinatorial Optimization
por: Davis, Ethan
Publicado: (2025)

Evolutionary Alternating Direction Method of Multipliers for Constrained Multi-Objective Optimization with Unknown Constraints
por: Li, Shuang, et al.
Publicado: (2024)

LLM4CMO: Large Language Model-aided Algorithm Design for Constrained Multiobjective Optimization
por: Chen, Zhen-Song, et al.
Publicado: (2025)

Deep Reinforcement Learning-Assisted Component Auto-Configuration of Differential Evolution Algorithm for Constrained Optimization: A Foundation Model
por: Yang, Xu, et al.
Publicado: (2025)

Visual Evolutionary Optimization on Graph-Structured Combinatorial Problems with MLLMs: A Case Study of Influence Maximization
por: Zhao, Jie, et al.
Publicado: (2025)

An Analysis of the Preferences of Distribution Indicators in Evolutionary Multi-Objective Optimization
por: Falcón-Cardona, Jesús Guillermo, et al.
Publicado: (2024)

A RankNet-Inspired Surrogate-Assisted Hybrid Metaheuristic for Expensive Coverage Optimization
por: Wu, Tongyu, et al.
Publicado: (2025)

Meta-Black-Box Optimization Can Do Search Guidance for Expensive Constrained Multi-Objective Optimization
por: Du, Yukun, et al.
Publicado: (2026)

A Universal Framework for Large-Scale Multi-Objective Optimization Based on Particle Drift and Diffusion
por: Li, Jia-Cheng, et al.
Publicado: (2025)

An Efficient Approach for Solving Expensive Constrained Multiobjective Optimization Problems
por: Rahi, Kamrul Hasan
Publicado: (2024)

Tiered Acquisition for Constrained Bayesian Optimization: An Application to Analog Circuits
por: Rashid, Ria, et al.
Publicado: (2024)

An Instance Space Analysis of Constrained Multi-Objective Optimization Problems
por: Alsouly, Hanan, et al.
Publicado: (2022)

Deep Reinforcement Learning-Assisted Automated Operator Portfolio for Constrained Multi-objective Optimization
por: Shao, Shuai, et al.
Publicado: (2026)

Multi-start Optimization Method via Scalarization based on Target Point-based Tchebycheff Distance for Multi-objective Optimization
por: Nagakane, Kota, et al.
Publicado: (2025)

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization
por: Gu, Shengda, et al.
Publicado: (2025)

Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
por: Li, Ke, et al.
Publicado: (2024)

MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization
por: Garmendia, Andoni I., et al.
Publicado: (2024)

UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
por: Zheng, Zhi, et al.
Publicado: (2024)

Multi-Objective Evolutionary Optimization of Chance-Constrained Multiple-Choice Knapsack Problems with Implicit Probability Distributions
por: Li, Xuanfeng, et al.
Publicado: (2026)

UDE-III: An Enhanced Unified Differential Evolution Algorithm for Constrained Optimization Problems
por: Trivedi, Anupam, et al.
Publicado: (2024)

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
por: Reijnen, Robbert, et al.
Publicado: (2025)

Enabling Population-Based Architectures for Neural Combinatorial Optimization
por: Garmendia, Andoni Irazusta, et al.
Publicado: (2026)

Ant Colony Sampling with GFlowNets for Combinatorial Optimization
por: Kim, Minsu, et al.
Publicado: (2024)

Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
por: Jiang, Tao, et al.
Publicado: (2025)

Rethinking Selection in Generational Genetic Algorithms to Solve Combinatorial Optimization Problems: An Upper Bound-based Parent Selection Strategy for Recombination
por: Sankaran, Prashant, et al.
Publicado: (2024)