Ant-inspired metaheuristic algorithms for combinatorial optimization problems in water resources management
R Bhavya, L Elango - Water, 2023 - mdpi.com
Ant-inspired metaheuristic algorithms known as ant colony optimization (ACO) offer an
approach that has the ability to solve complex problems in both discrete and continuous …
approach that has the ability to solve complex problems in both discrete and continuous …
Interactive machine learning: experimental evidence for the human in the algorithmic loop: A case study on Ant Colony Optimization
Recent advances in automatic machine learning (aML) allow solving problems without any
human intervention. However, sometimes a human-in-the-loop can be beneficial in solving …
human intervention. However, sometimes a human-in-the-loop can be beneficial in solving …
A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
The goal of Machine Learning to automatically learn from data, extract knowledge and to
make decisions without any human intervention. Such automatic (aML) approaches show …
make decisions without any human intervention. Such automatic (aML) approaches show …
Characterizing application sensitivity to OS interference using kernel-level noise injection
KB Ferreira, P Bridges… - SC'08: Proceedings of the …, 2008 - ieeexplore.ieee.org
Operating system noise has been shown to be a key limiter of application scalability in high-
end systems. While several studies have attempted to quantify the sources and effects of …
end systems. While several studies have attempted to quantify the sources and effects of …
Towards interactive Machine Learning (iML): applying ant colony algorithms to solve the traveling salesman problem with the human-in-the-loop approach
Abstract Most Machine Learning (ML) researchers focus on automatic Machine Learning
(aML) where great advances have been made, for example, in speech recognition …
(aML) where great advances have been made, for example, in speech recognition …
[PDF][PDF] Solving traveling salesman problem by using improved ant colony optimization algorithm
Z Hlaing, MA Khine - International Journal of Information and …, 2011 - academia.edu
Ant colony optimization (ACO) is a heuristic algorithm which has been proven a successful
technique and applied to a number of combinatorial optimization problems and is taken as …
technique and applied to a number of combinatorial optimization problems and is taken as …
The generalized traveling salesman problem solved with ant algorithms
Abstract A well known NP NP-hard problem called the generalized traveling salesman
problem (GTSP) is considered. In GTSP the nodes of a complete undirected graph are …
problem (GTSP) is considered. In GTSP the nodes of a complete undirected graph are …
The combination of ant colony optimization (ACO) and tabu search (TS) algorithm to solve the traveling salesman problem (TSP)
RW Dewantoro, P Sihombing - 2019 3rd International …, 2019 - ieeexplore.ieee.org
In this research, the authors want to propose the combination of Ant Colony Optimization
Algorithm and Tabu Search Algorithm as local search to solve Traveling Salesman Problem …
Algorithm and Tabu Search Algorithm as local search to solve Traveling Salesman Problem …
[PDF][PDF] An ant colony optimization algorithm for solving traveling salesman problem
ZCSS Hlaing, MA Khine - 2011 - meral.edu.mm
Abstract Ant Colony Optimization (ACO) is a class of heuristic search algorithms that have
been successfully applied to solving combinational optimization (CO) problems. The …
been successfully applied to solving combinational optimization (CO) problems. The …
[图书][B] Advances in bio-inspired computing for combinatorial optimization problems
CM Pintea - 2014 - Springer
” Advances in Bio-inspired Combinatorial Optimization Problems” illustrates several recent
bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired …
bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired …