A Hybrid Ant Colony Optimization Algorithm Based Lambda-Iteration Method for Unit Commitment Problem

2010 ◽  
Author(s):  
Derong Yu ◽  
Yongqiang Wang ◽  
Rui Guo
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Iteration Method ◽  
Unit Commitment ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals Comparison of the Probabilistic Ant Colony Optimization Algorithm and Some Iteration Method in Application for Solving the Inverse Problem on Model With the Caputo Type Fractional Derivative

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 555
Author(s):  
Rafał Brociek ◽  
Agata Chmielowska ◽  
Damian Słota
Keyword(s):  
Fractional Derivative ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Iteration Method ◽  
Heat Conduction Problem ◽  
Inverse Heat Conduction Problem ◽  
Ant Colony ◽  
Inverse Heat Conduction ◽  
Ant Colony Optimization Algorithm ◽  
Undetermined Coefficient

This paper presents the algorithms for solving the inverse problems on models with the fractional derivative. The presented algorithm is based on the Real Ant Colony Optimization algorithm. In this paper, the examples of the algorithm application for the inverse heat conduction problem on the model with the fractional derivative of the Caputo type is also presented. Based on those examples, the authors are comparing the proposed algorithm with the iteration method presented in the paper: Zhang, Z. An undetermined coefficient problem for a fractional diffusion equation. Inverse Probl. 2016, 32.

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

2012 ◽  
Vol 12 (1) ◽  
pp. 145-160 ◽  
Author(s):  
C. Christopher Columbus ◽  
K. Chandrasekaran ◽  
Sishaj P. Simon
Keyword(s):  
Ant Colony Optimization ◽  
Unit Commitment ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Commitment Problem

Study on the Application of Simulated Evolutionary Optimization Algorithm in Optimizing the Combination of Unit Commitments in Power System

2011 ◽  
Vol 48-49 ◽  
pp. 1186-1190
Author(s):  
Qing Song Liu ◽  
Jia Tong ◽  
Yi Feng Li
Keyword(s):  
Power System ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Unit Commitment ◽  
Evolutionary Optimization ◽  
Ant Colony ◽  
Feasible Region ◽  
Retrieval Process ◽  
Ant Colony Optimization Algorithm

This study adopted a simulated evolutionary optimization algorithm, ant colony optimization algorithm to find the optimal unit commitment operation. The concepts such as status, strategy, and path, etc. were introduced to devise the optimization of unit commitment operation by ant colony optimization algorithm mode, so that the optimal unit commitment operation could be found by ant colony optimization algorithm. To cope with different constraints by additional penalties and restrict the statuses not satisfying the constraints by tabu table, the retrieval of ant colony optimization algorithm could always be performed in feasible region and the retrieval process of the algorithm was effectively conducted. It is feasible and efficient to find the optimal unit commitment operation by ant colony optimization algorithm, which was proved by stimulation.

scholarly journals A Novel Binary Ant Colony Optimization: Application to the Unit Commitment Problem of Power Systems

2011 ◽  
Vol 6 (2) ◽  
pp. 174-181 ◽  
Author(s):  
Se-Hwan Jang ◽  
Jae-Hyung Roh ◽  
Wook Kim ◽  
Tenzi Sherpa ◽  
Jin-Ho Kim ◽  
...  
Keyword(s):  
Power Systems ◽  
Ant Colony Optimization ◽  
Unit Commitment ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Commitment Problem
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