Candidate Set Strategies for Ant Colony Optimisation
نویسندگان
چکیده
Ant Colony Optimisation based solvers systematically scan the set of possible solution elements before choosing a particular one. Hence, the computational time required for each step of the algorithm can be large. One way to overcome this is to limit the number of element choices to a sensible subset, or candidate set. This paper describes some novel generic candidate set strategies and tests these on the travelling salesman and car sequencing problems. The results show that the use of candidate sets helps to find competitive solutions to the test problems in a relatively short amount of time.
منابع مشابه
Candidate Set Parallelization Strategies for Ant Colony Optimization on the GPU
For solving large instances of the Travelling Salesman Problem (TSP), the use of a candidate set (or candidate list) is essential to limit the search space and reduce the overall execution time when using heuristic search methods such as Ant Colony Optimisation (ACO). Recent contributions have implemented ACO in parallel on the Graphics Processing Unit (GPU) using NVIDIA CUDA but struggle to ma...
متن کاملAdaptive Neighbourhood Search for the Component Deployment Problem
Since the establishment of the area of search-based software engineering, a wide range of optimisation techniques have been applied to automate various stages of software design and development. Architecture optimisation is one of the aspects that has been automated with methods like genetic algorithms, local search, and ant colony optimisation. A key challenge with all of these approaches is t...
متن کاملAnt Colony Optimisation for Stylometry: The Federalist Papers
This paper describes the use of Ant Colony Optimisation for the classification of works of disputed authorship, in this case the Federalist Papers.Classification accuracy was 79.1%, which compares reasonably well with previous work on the same data set using neural networks and genetic algorithms. Although statistical approaches have performed much better than this, the advantage of a rule-base...
متن کاملNiching for Ant Colony Optimisation
Evolutionary Computation niching methods, such as Fitness Sharing and Crowding, are aimed at simultaneously locating and maintaining multiple optima to increase search robustness, typically in multi-modal function optimization. Such methods have been shown to be useful for both single and multiple objective optimisation problems. Niching methods have been adapted in recent years for other optim...
متن کاملGeneric techniques in general purpose GPU programming with applications to ant colony and image processing algorithms
In 2006 NVIDIA introduced a new unified GPU architecture facilitating generalpurpose computation on the GPU. The following year NVIDIA introduced CUDA, a parallel programming architecture for developing general purpose applications for direct execution on the new unified GPU. CUDA exposes the GPU’s massively parallel architecture of the GPU so that parallel code can be written to execute much f...
متن کامل