7 citations · 7 across the 4 of their papers we have counts for
5 papers
MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design
Zishang Qiu, Xinan Chen, Rong Qu +1
Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthesis. In LLM-based AHD, the LLM reasons…
Preference-Agile Multi-Objective Optimization for Real-time Vehicle Dispatching
Jiahuan Jin, Wenhao Zhao, Rong Qu +4
Multi-objective optimization (MOO) has been widely studied in literature because of its versatility in human-centered decision making in real-life applications. Recently, demand fo…
MeLA: A Metacognitive LLM-Driven Architecture for Automatic Heuristic Design
Zishang Qiu, Xinan Chen, Long Chen +1
This paper introduces MeLA, a Metacognitive LLM-Driven Architecture that presents a new paradigm for Automatic Heuristic Design (AHD). Traditional evolutionary methods operate dire…
PGU-SGP: A Pheno-Geno Unified Surrogate Genetic Programming For Real-life Container Terminal Truck Scheduling
Leshan Tan, Chenwei Jin, Xinan Chen +2
Data-driven genetic programming (GP) has proven highly effective in solving combinatorial optimization problems under dynamic and uncertain environments. A central challenge lies i…
Analytics and Machine Learning in Vehicle Routing Research
Ruibin Bai, Xinan Chen, Zhi-Long Chen +13
The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle…