11 citations · 30 across the 18 of their papers we have counts for
18 papers
LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization
Mingen Kuang, Xudong Deng, Xi Lin +3
While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing methods typically generate and evolve heuristics as a single operator o…
MIRROR: A Multi-Agent Framework with Iterative Adaptive Revision and Hierarchical Retrieval for Optimization Modeling in Operations Research
Yifan Shi, Jiayi Wang, Minyi Wu +3
Operations Research (OR) relies on expert-driven modeling--a slow and fragile process ill-suited to novel scenarios. While large language models (LLMs) can automatically translate…
On the Effects of Smoothing Rugged Landscape by Different Toy Problems: A Case Study on UBQP
Wei Wang, Jialong Shi, Jianyong Sun +3
The hardness of the Unconstrained Binary Quadratic Program (UBQP) problem is due its rugged landscape. Various algorithms have been proposed for UBQP, including the Landscape Smoot…
A New Parallel Cooperative Landscape Smoothing Algorithm and Its Applications on TSP and UBQP
Wei Wang, Jialong Shi, Jianyong Sun +2
Combinatorial optimization problem (COP) is difficult to solve because of the massive number of local optimal solutions in his solution space. Various methods have been put forward…
Learning adaptive differential evolution algorithm from optimization experiences by policy gradient
Jianyong Sun, Xin Liu, Thomas Bäck +1
Differential evolution is one of the most prestigious population-based stochastic optimization algorithm for black-box problems. The performance of a differential evolution algorit…
Amortized Variational Deep Q Network
Haotian Zhang, Yuhao Wang, Jianyong Sun +1
Efficient exploration is one of the most important issues in deep reinforcement learning. To address this issue, recent methods consider the value function parameters as random var…