Swarm Intelligence Algorithms Modifications and Applications

This chapter presents a nature-inspired ant colony optimization (ACO) technique, along with its modified variants. The improved versions of this optimization technique are slightly different and effective than that of its standard version. ACO has inspired from the foraging behavior of ant colony an...

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Bibliographic Details
Main Author: Slowik, Adam
Format: eBook
Language:English
Published: United States CRC Press 2020
Taylor & Francis Group
Edition:1
Subjects:
Algorithms
Algorithms & Complexity
Computer Engineering
COMPUTERSCIENCEnetBASE
Data processing Computer science
ElectricalEngineeringnetBASE
ENGnetBASE
INFORMATIONSCIENCEnetBASE
Intelligent Systems
Mathematical optimization
monarch butterfly optimization
nature based optimization methods
nature inspired algorithms
SCI-TECHnetBASE
spotted hyena optimizer
STMnetBASE
Swarm intelligence
swarm intelligence algorithms
tutorial for swarm intelligence algorithms
Firefly Algorithm
Grey Wolf Optimization
BFO Algorithm
Chaotic Maps
ABC Algorithm
Original PSO Algorithm
Travelling Salesman Problem
Economic Load Dispatch Problem
Swarm Intelligence Algorithms
Real Life Optimization Problems
Levy Flights
Inertia Weights
Feasible Population
CSO
Optimal Power Flow Problem
Metaheuristic Optimization Algorithms
Real Power Loss Minimization
Limited Step Sizes
Standard ACO
PSO
CS
Test Distribution System
PSO Algorithm
Welded Beam Design Problem
Welded Beam Design
ISBN:0429749473, 9780429749476, 9781138391017, 9780367528881, 1138391018, 0367528886, 9780367496197, 0367496194
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Summary:This chapter presents a nature-inspired ant colony optimization (ACO) technique, along with its modified variants. The improved versions of this optimization technique are slightly different and effective than that of its standard version. ACO has inspired from the foraging behavior of ant colony and its capability to seek the shortest path between their nest and food source. This optimization method is based on a natural phenomena known as pheromone trails, a substance laid down by ants especially when carrying food so that their fellow ants can sense and follow this path. The new ants entering into the ant system will follow the path with highest pheromone concentration. In this chapter, a brief overview of standard ACO is presented, followed by different variants of ACO since its development. The application of the ACO technique for real-life optimization problems is demonstrated by solving an optimal shunt capacitor allocation problem of 33-bus test distribution system for power loss minimization.
ISBN:0429749473
9780429749476
9781138391017
9780367528881
1138391018
0367528886
9780367496197
0367496194
DOI:10.1201/9780429422607