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Found 8 papers, 4 papers with code
Self-Improved Learning for Scalable Neural Combinatorial Optimization
The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design.
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
The results show that the unified model demonstrates superior performance in the eleven VRPs, reducing the average gap to around 5% from over 20% in the existing approach and achieving a significant performance boost on benchmark datasets as well as a real-world logistics application.
An Example of Evolutionary Computation + Large Language Model Beating Human: Design of Efficient Guided Local Search
Recently, we have proposed a novel Algorithm Evolution using Large Language Model (AEL) framework for automatic algorithm design.
Algorithm Evolution Using Large Language Model
In this paper, we propose a novel approach called Algorithm Evolution using Large Language Model (AEL).
Large Language Model for Multi-objective Evolutionary Optimization
It is also promising to see the operator only learned from a few instances can have robust generalization performance on unseen problems with quite different patterns and settings.
Heuristics for Vehicle Routing Problem: A Survey and Recent Advances
Vehicle routing is a well-known optimization research topic with significant practical importance.
A Data-Driven Column Generation Algorithm For Bin Packing Problem in Manufacturing Industry
The bin packing problem exists widely in real logistic scenarios (e. g., packing pipeline, express delivery), with its goal to improve the packing efficiency and reduce the transportation cost.
Introduction to The Dynamic Pickup and Delivery Problem Benchmark -- ICAPS 2021 Competition
The Dynamic Pickup and Delivery Problem (DPDP) is an essential problem within the logistics domain.
