13 citations · 14 across the 12 of their papers we have counts for
13 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…
Decoupling Numerical and Structural Parameters: An Empirical Study on Adaptive Genetic Algorithms via Deep Reinforcement Learning for the Large-Scale TSP
Hongyu Wang, Yuhan Jing, Yibing Shi +3
Proper parameter configuration is a prerequisite for the success of Evolutionary Algorithms (EAs). While various adaptive strategies have been proposed, it remains an open question…
TIDE: Tuning-Integrated Dynamic Evolution for LLM-Based Automated Heuristic Design
Chentong Chen, Mengyuan Zhong, Ye Fan +2
Although Large Language Models have advanced Automated Heuristic Design, treating algorithm evolution as a monolithic text generation task overlooks the coupling between discrete a…
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…
Vibroseis Vehicle Routing Problem with Spatio-Temporal Coupled Constraints
Kexin Zhu, Jialong Shi, Jianyong Sun +3
Simultaneous multi vibroseis vehicle operations are central to modern land seismic exploration and can be modeled as a Vehicle Routing Problem (VRP). A critical distinction from cl…
HiFo-Prompt: Prompting with Hindsight and Foresight for LLM-based Automatic Heuristic Design
Chentong Chen, Mengyuan Zhong, Ye Fan +2
LLM-based Automatic Heuristic Design (AHD) within Evolutionary Computation (EC) frameworks has shown promising results. However, its effectiveness is hindered by the use of static…
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…
Multi-objectivization Inspired Metaheuristics for the Sum-of-the-Parts Combinatorial Optimization Problems
Jialong Shi, Jianyong Sun, Qingfu Zhang
Multi-objectivization is a term used to describe strategies developed for optimizing single-objective problems by multi-objective algorithms. This paper focuses on multi-objectiviz…
Homotopic Convex Transformation: A New Landscape Smoothing Method for the Traveling Salesman Problem
Jialong Shi, Jianyong Sun, Qingfu Zhang +1
This paper proposes a novel landscape smoothing method for the symmetric Traveling Salesman Problem (TSP). We first define the Homotopic Convex (HC) transformation of a TSP as a co…
EB-GLS: An Improved Guided Local Search Based on the Big Valley Structure
Jialong Shi, Qingfu Zhang, Edward Tsang
Local search is a basic building block in memetic algorithms. Guided Local Search (GLS) can improve the efficiency of local search. By changing the guide function, GLS guides a loc…
PPLS/D: Parallel Pareto Local Search based on Decomposition
Jialong Shi, Qingfu Zhang, Jianyong Sun
Pareto Local Search (PLS) is a basic building block in many metaheuristics for Multiobjective Combinatorial Optimization Problem (MCOP). In this paper, an enhanced PLS variant call…
A New Cooperative Framework for Parallel Trajectory-Based Metaheuristics
Jialong Shi, Qingfu Zhang
In this paper, we propose the Parallel Elite Biased framework (PEB framework) for parallel trajectory-based metaheuristics. In the PEB framework, multiple search processes are exec…