An Improved Ant Colony Optimization with Subpath-Based Pheromone Modification Strategy

Deng, Xiangyang; Zhang, Limin; Feng, Jiawen

doi:10.1007/978-3-319-61824-1_28

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Improvement By Applying Pheromones Update1

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2021

2024

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Cited by 2 publications

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“…Deng et al [25] proposed a new pheromone updating rule, known as SPB (sub-path-based pheromone modification) 'rule and suggested an improved ACO based on the SPB rule, naturally named' as SPB-ACO. The SPB rule comprises an adaptive part and an iterative updating part.…”

Section: Improvement By Applying Pheromones Updatementioning

confidence: 99%

Recent research in finding the optimal path by ant colony optimization

Sari

Mohamad

2021

Bulletin EEI

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The computation of the optimal path is one of the critical problems in graph theory. It has been utilized in various practical ranges of real world applications including image processing, file carving and classification problem. Numerous techniques have been proposed in finding optimal path solutions including using ant colony optimization (ACO). This is a nature-inspired metaheuristic algorithm, which is inspired by the foraging behavior of ants in nature. Thus, this paper study the improvement made by many researchers on ACO in finding optimal path solution. Finally, this paper also identifies the recent trends and explores potential future research directions in file carving.

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Section: Improvement By Applying Pheromones Updatementioning

confidence: 99%