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02/08/2023
Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks
Algorithm selection is a well-known problem where researchers investigat...
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02/01/2023
Digital Twin Applications in Urban Logistics: An Overview
Urban traffic attributed to commercial and industrial transportation is ...
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11/01/2022
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems
Multi-objective evolutionary algorithms (MOEAs) are widely used to solve...
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05/20/2022
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens
It is increasingly common to solve combinatorial optimisation problems t...
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01/25/2022
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems
This paper reports on the first international competition on AI for the ...
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06/08/2021
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
Surrogate algorithms such as Bayesian optimisation are especially design...
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11/06/2020
Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems
One method to solve expensive black-box optimization problems is to use ...
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06/08/2020
Black-box Mixed-Variable Optimisation using a Surrogate Model that Satisfies Integer Constraints
A challenging problem in both engineering and computer science is that o...
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11/20/2019
Black-box Combinatorial Optimization using Models with Integer-valued Minima
When a black-box optimization objective can only be evaluated with costl...
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03/31/2016
Online Optimization with Costly and Noisy Measurements using Random Fourier Expansions
This paper analyzes DONE, an online optimization algorithm that iterativ...
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09/19/2013
Exploration and Exploitation in Visuomotor Prediction of Autonomous Agents
This paper discusses various techniques to let an agent learn how to pre...
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08/29/2013
