The Application of Virtual Machine Placement Using Fuzzy Grouping Genetic Algorithm

Journal of Advances in Information Technology, Journal Year: 2025, Volume and Issue: 16(2), P. 189 - 197

Published: Jan. 1, 2025

Language: Английский

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A Review of Ant Colony Optimization for Solving 0-1 Knapsack and Traveling Salesman Problems

Deleted Journal, Journal Year: 2025, Volume and Issue: 3(2), P. 87 - 99

Published: March 10, 2025

Ant Colony Optimization (ACO) represents a widespread nature-based metaheuristic algorithm which solves combinatorial optimization problems effectively [1]. This research study examines ACO-based solutions for Traveling Salesman Problem (TSP) and 0-1 Knapsack (0-1 KP) are both identified as NP-hard problems. ACO successfully achieves near-optimal because it duplicates real ants' pheromone-based foraging approach operates between exploration exploitation modes effectively. review discusses methods solving complex through discussion of modern solution their evaluation results performance benefits over basic approaches. section presents challenges include computational complexity two additional hybrid models while exploring adaptive parameter adjustments well quantum-inspired optimizations [2]. The development aims at combining this with deep learning reinforcement approaches to boost its operational speed practical across dynamic contexts. findings suggest that remains promising technique vast potential large-scale in various domains [3].

Language: Английский

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CHPSO: An Efficient Algorithm for Task Scheduling and Optimizing Resource Utilization in the Cloud Environment

Journal of Grid Computing, Journal Year: 2025, Volume and Issue: 23(2)

Published: April 1, 2025

Language: Английский

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Optimization of UAV Flight Paths in Multi-UAV Networks for Efficient Data Collection

Arabian Journal for Science and Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: July 29, 2024

Language: Английский

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A Hybrid Algorithm Based on PSO Algorithm and Chi-Squared Distribution for Tasks Consolidation in Cloud Computing Environment

Published: Nov. 21, 2023

In order to maximize the effectiveness and performance of cloud computing systems, this study focuses on addressing challenges workload balancing resource utilization in scheduling. Workload plays a crucial role ensuring that workloads are evenly distributed across available resources, thereby reducing likelihood constraints enhancing system performance. On other hand, aims utilize processing power, memory, network bandwidth their fullest capacity, resulting improved efficacy cost-effectiveness infrastructure. To tackle these challenges, we propose novel optimization technique called CHPSO (Chi-squared Particle Swarm Optimization) context. The proposed algorithm demonstrates its optimizing compared algorithms such as PSO (Particle CS (Cuckoo Search).

Language: Английский

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Hybrid Metaheuristic Algorithms for Resource Allocation in Fog Computing Environments

Published: Feb. 21, 2024

This study aims to investigate the feasibility concerns of metaheuristic algorithms involving a hybridisation among GPSO, Adventure, ACO-GA and FDE; for asset allocation with regard fog computing context. These evaluations were based on joining speed, arrangement quality, flexibility strength in wide testing. Comparative analysis was performed, execution their related works within field. It is inferred that demonstrates fantastic meeting speed; code needs 450 cycles do this well has high greatness or fitness zero. 92ocuments GPSO FDE are closely proximate, showing competitive coalescence along design optimization. Adventure programs feature slightly less intense encounters but present dynamic exploration-exploitation prospects. In case if adaptability, trumps score 92% highlighting its resilience larger datasets. Stability reveals have little deviation folds, stability. The discoveries emphasize nuanced qualities each algorithm, giving profitable bits knowledge professionals computing. results contribute progressing talk allotment, directing future research towards refinement application hybrid calculations energetic situations.

Language: Английский

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Feature Selection Based on Binary Tree Growth Algorithm Using Opposition-Based Learning

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 263 - 275

Published: Jan. 1, 2024

Language: Английский

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