Parallel metaheuristics: recent advances and new trends
The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …
and needs that researchers have been encountering. In the last decade, new models of …
A survey on GPU-based implementation of swarm intelligence algorithms
Inspired by the collective behavior of natural swarm, swarm intelligence algorithms (SIAs)
have been developed and widely used for solving optimization problems. When applied to …
have been developed and widely used for solving optimization problems. When applied to …
A survey on parallel ant colony optimization
Ant colony optimization (ACO) is a well-known swarm intelligence method, inspired in the
social behavior of ant colonies for solving optimization problems. When facing large and …
social behavior of ant colonies for solving optimization problems. When facing large and …
[HTML][HTML] Parallel ant colony optimization on multi-core SIMD CPUs
Y Zhou, F He, N Hou, Y Qiu - Future Generation Computer Systems, 2018 - Elsevier
Ant colony optimization (ACO) is a population-based metaheuristic for solving hard
combinatorial optimization problems. Many studies are dedicated to accelerating ACO by …
combinatorial optimization problems. Many studies are dedicated to accelerating ACO by …
An adapted ant colony optimization algorithm for the minimization of the travel distance of pickers in manual warehouses
R De Santis, R Montanari, G Vignali… - European Journal of …, 2018 - Elsevier
This paper proposes a new metaheuristic routing algorithm for the minimization of the travel
distance of pickers in manual warehouses. The algorithm is based on the ant colony …
distance of pickers in manual warehouses. The algorithm is based on the ant colony …
Dynamic strategy based parallel ant colony optimization on GPUs for TSPs
Y Zhou, F He, Y Qiu - Science China Information Sciences, 2017 - Springer
Metaheuristics are a type of approximate optimization algorithms for solving hard and
complex problems in science and engineering [1]. They can be defined as algorithm …
complex problems in science and engineering [1]. They can be defined as algorithm …
Parallel ant colony optimization on graphics processing units
A Delévacq, P Delisle, M Gravel, M Krajecki - Journal of Parallel and …, 2013 - Elsevier
The purpose of this paper is to propose effective parallelization strategies for the Ant Colony
Optimization (ACO) metaheuristic on Graphics Processing Units (GPUs). The Max–Min Ant …
Optimization (ACO) metaheuristic on Graphics Processing Units (GPUs). The Max–Min Ant …
Improving Ant Colony Optimization performance on the GPU using CUDA
We solve the Travelling Salesman Problem (TSP) using a parallel implementation of the Ant
System (AS) algorithm for execution on the Graphics Processing Unit (GPU) using NVIDIA …
System (AS) algorithm for execution on the Graphics Processing Unit (GPU) using NVIDIA …
Parallel computational optimization in operations research: A new integrative framework, literature review and research directions
G Schryen - European Journal of Operational Research, 2020 - Elsevier
Solving optimization problems with parallel algorithms has a long tradition in OR. Its future
relevance for solving hard optimization problems in many fields, including finance, logistics …
relevance for solving hard optimization problems in many fields, including finance, logistics …
A parallel ant colony optimization algorithm with GPU-acceleration based on all-in-roulette selection
J Fu, L Lei, G Zhou - Third International Workshop on …, 2010 - ieeexplore.ieee.org
Ant Colony Optimization is computationally expensive when it comes to complex problems.
The Jacket toolbox allows implementation of MATLAB programs in Graphics Processing Unit …
The Jacket toolbox allows implementation of MATLAB programs in Graphics Processing Unit …