4.7 Article

Automatic generation of a hybrid algorithm for the maximum independent set problem using genetic programming

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection

Isaias I. Huerta et al.

Summary: This work introduces a new metaheuristic for solving the Traveling Salesman Problem, using an Automatic Algorithm Selection model and convolutional neural network to predict solver rankings. Results show that the time needed to predict the best solver has been significantly reduced compared to traditional methods, and the metasolver achieves an accuracy of 79.8% across various datasets.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Computer Science, Artificial Intelligence

A differentiable approach to the maximum independent set problem using dataless neural networks

Ismail R. Alkhouri et al.

Summary: This paper introduces a new approach that does not require training data for neural networks to address combinatorial optimization problems. Experimental results show that this method performs well for large-scale graphs without the need for training data.

NEURAL NETWORKS (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Dynamic Approximate Maximum Independent Set on Massive Graphs

Xiangyu Gao et al.

Summary: This paper focuses on the problem of maintaining a maximum independent set on dynamic graphs. A framework is proposed to approximate the maximum independent set, and two dynamic algorithms with different complexities are implemented. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithms.

2022 IEEE 38TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2022) (2022)

Article Computer Science, Artificial Intelligence

Combinatorial optimization with physics-inspired graph neural networks

Martin J. A. Schuetz et al.

Summary: This paper demonstrates the application of graph neural networks to solve combinatorial optimization problems. By applying relaxation strategy to the problem Hamiltonian and training a graph neural network with unsupervised learning, we are able to achieve comparable or even superior performance to existing solvers on classical NP-hard problems, and scale beyond the state of the art to problems with millions of variables.

NATURE MACHINE INTELLIGENCE (2022)

Article Management

Conflict resolving - A local search algorithm for solving large scale conflict graphs in freight railway timetabling

Julian Reisch et al.

Summary: This paper addresses the simultaneous planning of the annual timetable for all freight trains in Germany, introducing a column generation method to solve the Train Path Assignment Problem (TPAP). By utilizing the Conflict Resolving (CR) algorithm and simulated annealing framework, large-scale Maximum Independent Set problem instances can be effectively handled.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2021)

Article Computer Science, Interdisciplinary Applications

Automatic generation of algorithms for robust optimisation problems using Grammar-Guided Genetic Programming

Martin Hughes et al.

Summary: The study develops algorithms to tackle robust black-box optimization problems with limited model runs. By employing an automatic generation of algorithms approach, a novel heuristic solution space is investigated, resulting in algorithms that improve upon current state of the art. The component level breakdowns of the populations of algorithms developed are also analyzed to identify high-performing heuristic components for robust problems.

COMPUTERS & OPERATIONS RESEARCH (2021)

Letter Computer Science, Information Systems

On the analysis of ant colony optimization for the maximum independent set problem

Xiaoyun Xia et al.

FRONTIERS OF COMPUTER SCIENCE (2021)

Article Computer Science, Artificial Intelligence

Automatic design of specialized algorithms for the binary knapsack problem

Nicolas Acevedo et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

Article Computer Science, Artificial Intelligence

The General Combinatorial Optimization Problem: Towards Automated Algorithm Design

Rong Qu et al.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2020)

Review Computer Science, Artificial Intelligence

Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review

J. Carrasco et al.

SWARM AND EVOLUTIONARY COMPUTATION (2020)

Article Computer Science, Software Engineering

ARJA: Automated Repair of Java Programs via Multi-Objective Genetic Programming

Yuan Yuan et al.

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING (2020)

Article Computer Science, Artificial Intelligence

Anytime automatic algorithm selection for knapsack

Isaias I. Huerta et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

Proceedings Paper Computer Science, Theory & Methods

Novel Algorithms Automatically Generated for Optimization Problems

Moises Silva-Munoz et al.

2019 38TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC) (2019)

Article Computer Science, Artificial Intelligence

Genetic Programming Proof Search Automatic Improvement

Zoltan A. Kocsis et al.

JOURNAL OF AUTOMATED REASONING (2018)

Article Computer Science, Artificial Intelligence

Finding near-optimal independent sets at scale

Sebastian Lamm et al.

JOURNAL OF HEURISTICS (2017)

Article Computer Science, Artificial Intelligence

Evolution of new algorithms for the binary knapsack problem

Lucas Parada et al.

NATURAL COMPUTING (2016)

Article Computer Science, Artificial Intelligence

Evolution of new algorithms for the binary knapsack problem

Lucas Parada et al.

NATURAL COMPUTING (2016)

Article Engineering, Multidisciplinary

Automatic design of algorithms for the traveling salesman problem

Cristian Loyola et al.

COGENT ENGINEERING (2016)

Article Automation & Control Systems

General swap-based multiple neighborhood tabu search for the maximum independent set problem

Yan Jin et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2015)

Proceedings Paper Computer Science, Artificial Intelligence

Automatic design of algorithms for optimization problems

Carlos Contreras-Bolton et al.

2015 LATIN AMERICA CONGRESS ON COMPUTATIONAL INTELLIGENCE (LA-CCI) (2015)

Article Computer Science, Artificial Intelligence

NuMVC: An Efficient Local Search Algorithm for Minimum Vertex Cover

Shaowei Cai et al.

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH (2013)

Article Multidisciplinary Sciences

Automatically Generated Algorithms for the Vertex Coloring Problem

Carlos Contreras Bolton et al.

PLOS ONE (2013)

Article Computer Science, Artificial Intelligence

Fast local search for the maximum independent set problem

Diogo V. Andrade et al.

JOURNAL OF HEURISTICS (2012)

Article Computer Science, Artificial Intelligence

A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms

Joaquin Derrac et al.

SWARM AND EVOLUTIONARY COMPUTATION (2011)

Article Biochemical Research Methods

Uniform integration of genome mapping data using intersection graphs

E Harley et al.

BIOINFORMATICS (2001)