Book Chapter10.1007/978-981-15-0214-9_12
Artificial Intelligence Based Optimization Techniques: A Review
Agrani Swarnkar,Anil Swarnkar +1 more
- 01 Jan 2020
- pp 95-103
24
TL;DR: This paper provides a brief review of some of the well-known optimization techniques, e.g., Genetic Algorithm, Particle Swarm Al algorithm, and Ant Colony Optimization and recently developed techniques, E.g. BAT Algorithm and Elephant Herding Optimization.
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Abstract: Many artificial intelligence based optimization techniques have been introduced since the early 60s. This paper provides a brief review of some of the well-known optimization techniques, e.g., Genetic Algorithm, Particle Swarm Algorithm, and Ant Colony Optimization and recently developed techniques, e.g., BAT Algorithm and Elephant Herding Optimization. All these techniques are population-based search algorithms, in which the initial population is created randomly initializing input parameters within the specified range. They approach toward the best solution inspired by the behavior of natural entities. All of these techniques have a potential to provide optimal or near-optimal solutions.
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Citations
Distribution System Minimum Loss Reconfiguration in the Hyper Cube Ant Colony Optimization Framework
Enrico Carpaneto,Gianfranco Chicco +1 more
- 01 Jan 2006
TL;DR: In this article, the authors presented an original application of the Ant Colony Optimization concepts to the optimal reconfiguration of distribution systems, with the objective of minimizing the distribution system losses in the presence of a set of structural and operational constraints.
90
A Comprehensive Review on Protection Strategies to Mitigate the Impact of Renewable Energy Sources on Interconnected Distribution Networks
Muhammad Usama,Hazlie Mokhlis,Mahmoud Moghavvemi,Nurulafiqah Nadzirah Mansor,Majed A. Alotaibi,Munir Azam Muhammad,Abdullah Akram Bajwa +6 more
TL;DR: In this paper, a comparative analysis of various protection techniques implemented to alleviate the impact of integrated resources into distribution networks is presented, and a comparison of classical and modified protection approaches in terms of advantages, shortcomings, and implementation costs is presented.
From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation
TL;DR: In this paper , a multilayer perceptron and a multiobjective genetic algorithm were used to analyze World Bank Open Data from 1960 to 2019, including 217 countries, to find patterns that are not easy to detect, which include multiple non-linear relationships.
68
An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks
TL;DR: This paper proposes a quorum-based grid system where the number of sensors in the quorum is increased without actually increasing quorums themselves, leading to improvements in throughput and latency by 14.23%.
•Posted Content
InTAS - The Ingolstadt Traffic Scenario for SUMO.
TL;DR: The concept, model, and validation for InTAS are presented, a realistic traffic scenario for Ingolstadt, and the scenario was validated by comparing real-traffic data from 24 measurement points with InTas simulation results.
References
Genetic algorithms in search, optimization and machine learning
David E. Goldberg
- 01 Jan 1989
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
58.6K
•Book
Genetic algorithms in search, optimization, and machine learning
David E. Goldberg
- 01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Particle swarm optimization
James Kennedy,Russell C. Eberhart +1 more
- 06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
44.1K
•Book
Adaptation in natural and artificial systems
John H. Holland
- 01 Jan 1975
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Particle Swarm Optimization.
James Kennedy
- 01 Jan 2017
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
35K