Demand Side Management Using Harmony Search Algorithm and BAT Algorithm

2017 ◽  
pp. 191-202
Author(s):  
Mashab Farooqi ◽  
Muhammad Awais ◽  
Zain Ul Abdeen ◽  
Saadia Batool ◽  
Zunaira Amjad ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Bat Algorithm ◽  
Demand Side Management ◽  
Harmony Search Algorithm ◽  
Demand Side

A Comparative Study of Global-Best Harmony Search and Bat Algorithms on Optimization Problems

2013 ◽  
Vol 464 ◽  
pp. 352-357
Author(s):  
Pasura Aungkulanon
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Computation Time ◽  
Finite Sequence ◽  
Bat Algorithm ◽  
Harmony Search Algorithm ◽  
Response Surfaces ◽  
Sample Mean ◽  
Constrained Problems

The engineering optimization problems are large and complex. Effective methods for solving these problems using a finite sequence of instructions can be categorized into optimization and meta-heuristics algorithms. Meta-heuristics techniques have been proved to solve various real world problems. In this study, a comparison of two meta-heuristic techniques, namely, Global-Best Harmony Search algorithm (GHSA) and Bat algorithm (BATA), for solving constrained optimization problems was carried out. GHSA and BATA are optimization algorithms inspired by the structure of harmony improvisation search process and social behavior of bat echolocation for decision direction. These algorithms were implemented under different natures of three optimization, which are single-peak, multi-peak and curved-ridge response surfaces. Moreover, both algorithms were also applied to constrained engineering problems. The results from non-linear continuous unconstrained functions in the context of response surface methodology and constrained problems can be shown that Bat algorithm seems to be better in terms of the sample mean and variance of design points yields and computation time.

Convergence Parameter Analysis for Different Metaheuristic Methods Control Constant Estimation and it’s Tradeoff Inference

2015 ◽  
Vol 6 (2) ◽  
pp. 404
Author(s):  
R. Sagayaraj ◽  
S. Thangavel
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Bat Algorithm ◽  
Cuckoo Search ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Parameter Analysis ◽  
Heuristic Methods ◽  
Metaheuristic Methods ◽  
Control Constant

This paper is an extension of our previous work, which discussed the difficulty in implementing different methods of resistance emulation techniques on the hardware due to its control constant estimation delay. In order to get rid of the delay this paper attempts to include the meta-heuristic methods for the control constants of the controller. To achieve the minimum Total Harmonic Disturbance (THD) in the AC side of the converter modern meta-heuristic methods are compared with the traditional methods. The convergence parameters, which are primary for the earlier estimation of the control constants, are compared with the measured parameters, tabulated and tradeoff inference is done among the methods. This kind of implementation does not need the mathematical model of the system under study for finding the control constants. The parameters considered for estimation are population size, maximum number of epochs, and global best solution of the control constants, best THD value and execution time. MatlabTM /Simulink based simulation is optimized with the M-file based optimization techniques like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm and Bat Algorithm.

Optimal linear cooperation spectrum sensing method based on chaos harmony search algorithm

2013 ◽  
Vol 32 (9) ◽  
pp. 2412-2417
Author(s):  
Yue-hong LI ◽  
Pin WAN ◽  
Yong-hua WANG ◽  
Jian YANG ◽  
Qin DENG
Keyword(s):  
Spectrum Sensing ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Optimal Linear
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