An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle

Abstract To solve the operation sequencing problem in CAPP that is a difficult problem, combining the idea of genetic algorithm, an GA-Jaya algorithm is proposed to minimize the total cost. In the GA-Jaya, the population is initialized according to the procedure priority adjacency matrix which makes the population all meet the process priority relationship. Mutation iteration operator and two kinds of crossover iteration operator are designed for process sequence and processing resource evolution. The GA-Jaya algorithm is applied to a typical case, and compared with the existing genetic algorithm, particle swarm optimization algorithm and ant colony optimization algorithm. The results show that the average quality of the solution obtained by the GA-Jaya algorithm is better than the existing genetic algorithm, particle swarm optimization algorithm and ant colony optimization algorithm.

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Grid Task Scheduling Strategy Based on Particle Swarm Optimizationand Ant Colony Optimization Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.108-111.392 ◽

2010 ◽

Vol 108-111 ◽

pp. 392-397

Author(s):

Peng Cheng Wei ◽

Xi Shi

Keyword(s):

Particle Swarm Optimization ◽

Ant Colony Optimization ◽

Task Scheduling ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Scheduling Algorithm ◽

Particle Swarm ◽

Ant Colony ◽

Ant Colony Optimization Algorithm ◽

Swarm Optimization

Based on particle swarm optimization algorithm, this paper presents a grid scheduling optimization algorithm combing the advantages of Ant Colony optimization algorithm. The algorithm processes task scheduling through particle swarm optimization algorithm to get a group of relatively optimal solutions, and then conducts small-area local search with Ant Colony optimization algorithm. Theoretical analysis and results of the simulation experiments show that this scheduling algorithm effectively achieves load balancing of resources with comprehensive advantages in time efficiency and solution accuracy compared to the traditional Ant Colony optimization algorithm and particle swarm optimizationalgorithm, and can be applied to task scheduling in grid computing.

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Research on improved particle-swarm-optimization algorithm based on ant-colony-optimization algorithm

2017 29th Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc.2017.7978639 ◽

2017 ◽

Cited By ~ 3

Author(s):

Dong Li ◽

Huaitao Shi ◽

Jianchang Liu ◽

Shubin Tan ◽

Chi Li ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Ant Colony Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Ant Colony ◽

Ant Colony Optimization Algorithm ◽

Swarm Optimization ◽

Improved Particle Swarm Optimization

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Stability Enhancement of Transfer Function by Ant Colony Optimization and Particle Swarm Optimization Algorithm

International Journal of Current Engineering and Technology ◽

10.14741/ijcet/v.8.3.35 ◽

2018 ◽

Vol 8 (3) ◽

Author(s):

Chaman Yadav ◽

Prabha Singh ◽

Jaya Mishra ◽

Kushal Tiwari ◽

Shashank Singh

Keyword(s):

Particle Swarm Optimization ◽

Evolutionary Algorithms ◽

Ant Colony Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Optimization Problems ◽

Particle Swarm ◽

Ant Colony ◽

Swarm Optimization ◽

The Way

This paper presents the concepts of three evolutionary algorithms i.e, ant colony optimization and particle swarm optimization algorithm. An evolutionary algorithm copies the way how evolution occurs in the nature. There are various types of evolutionary algorithms. This paper focuses on ACO and PSO algorithms. ACO provides solution to various optimization problems. It follows the principle of survival of the fittest. Various problems such as knapsack problem, TSP(travelling salesman problem) can be solved using genetic algorithm. Ant colony optimization is a heuristic algorithm which follows the behaviour of ants i.e., the way ants seek food in their environment by starting from their nest. Particle swarm optimization algorithm (PSO) is also an optimization algorithm which also uses a method of searching using some heuristics.

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