scholarly journals Modified Cuckoo Search Algorithm: A Novel Method to Minimize the Fuel Cost

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1328 ◽  
Author(s):  
Thang Nguyen ◽  
Dieu Vo ◽  
Nguyen Vu Quynh ◽  
Le Van Dai
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Fuel Cost ◽  
Novel Method

scholarly journals Optimal Economic Load Dispatch using Multiobjective Cuckoo Search Algorithm

2018 ◽  
Vol 12 (1) ◽  
pp. 168 ◽  
Author(s):  
Z.M. Yasin ◽  
N.F.A. Aziz ◽  
N.A. Salim ◽  
N.A. Wahab ◽  
N.A. Rahmat
Keyword(s):  
Carbon Emission ◽  
Search Algorithm ◽  
Cost Minimization ◽  
Operating Cost ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Multiobjective Particle Swarm Optimization ◽  
Fuel Cost Minimization

In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques.

scholarly journals Cuckoo search algorithm to solve the problem of economic emission dispatch with the incorporation of facts devices under the valve-point loading effect

2021 ◽  
Vol 34 (4) ◽  
pp. 569-588
Author(s):  
Larouci Benyekhlef ◽  
Sitayeb Abdelkader ◽  
Boudjella Houari ◽  
Ayad Ahmed Nour El Islam
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Fuel Cost ◽  
Loading Effect ◽  
Facts Devices ◽  
Emission Dispatch ◽  
Valve Point Loading Effect ◽  
Economic Emission Dispatch

The essential objective of optimal power flow is to find a stable operating point which minimizes the cost of the production generators and its losses, and keeps the power system acceptable in terms of limits on the active and reactive powers of the generators. In this paper, we propose the nature-inspired Cuckoo search algorithm (CSA) to solve economic/emission dispatch problems with the incorporation of FACTS devices under the valve-point loading effect (VPE). The proposed method is applied on different test systems cases to minimize the fuel cost and total emissions and to see the influence of the integration of FACTS devices. The obtained results confirm the efficiency and the robustness of the Cuckoo search algorithm compared to other optimization techniques published recently in the literature. In addition, the simulation results show the advantages of the proposed algorithm for optimizing the production fuel cost, total emissions and total losses in all transmission lines.

Implementation of Smooth and Non-Smooth Fuel Cost Function for Economic Load Dispatch using Cuckoo Search Method

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Apurva Gautam ◽  
Anupam Masih
Keyword(s):  
Cost Function ◽  
Power Plants ◽  
Search Algorithm ◽  
Inequality Constraints ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Practical Applications ◽  
Equality And Inequality Constraints

Economic Load Dispatch (ELD) is an important topic in the operation of power plants which can help to build up effecting generating management plans. The ELD problem has no smooth cost function with equality and inequality constraints which make it difficult to be effectively solved. The paper presents an application of Cuckoo Search Algorithm (CSA) to solve Economic Load Dispatch (ELD) problems with smooth and non-smooth fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses over a certain period of time while relaxing various equality and inequality constraints. The unit Min/Max operational constraints, effects of valve-point loading ripples and line losses are considered for the practical applications. This paper describes the implementation of smooth and non smooth fuel cost function by CSA Method and its comparison with BAT method. We have used 6 and 12 bus system for calculating their total fuel cost.

scholarly journals A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision

2017 ◽  
Vol 20 (60) ◽  
pp. 51 ◽  
Author(s):  
Loubna Benchikhi ◽  
Mohamed Sadgal ◽  
Aziz Elfazziki ◽  
Fatimaezzahra Mansouri
Keyword(s):  
Computer Vision ◽  
Parameter Optimization ◽  
Expert Knowledge ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Novel Approach ◽  
Novel Method ◽  
Computer Vision Applications ◽  
Must Experiment

Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS) is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO), reinforcement learning (RL) and ant colony optimization (ACO) show the efficiency of this novel method.

scholarly journals Detection of copy-move image forgery using SVD and cuckoo search algorithm

2018 ◽  
Vol 7 (2.13) ◽  
pp. 79 ◽  
Author(s):  
Abhishek Kashyap ◽  
Megha Agarwal ◽  
Hariom Gupta
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Forgery Detection ◽  
Single Value Decomposition ◽  
Novel Method ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
Value Decomposition ◽  
Parameter Values

Copy-move Copy move forgery (CMF) is one of the straightforward strategies to create forged images. To detect this kind of forgery one of the widely used method is single value decomposition (SVD). Few methods based on SVD are most acceptable but some methods are less acceptable because these methods highly depend on those parameters value, which is manually selected depending upon the tampered images. For different images, we require different parameter values. In this paper, we have proposed a novel method, which uses both copy-move forgery detection using SVD and Cuckoo search (CS) algorithm. It utilizes Cuckoo search algorithm to generate customized parameter values for different tampered images, which are used in copy-move forgery detection (CMFD) under block based framework. 

scholarly journals Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

2019 ◽  
Vol 8 (11) ◽  
pp. 1893-1901
Keyword(s):  
Secret Sharing ◽  
Search Algorithm ◽  
Fitness Function ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Video Watermarking ◽  
Computational Time ◽  
Transform Domain ◽  
Optimization Function ◽  
Novel Method

Cuckoo search algorithm is an efficiently designed algorithm for optimization based on the behavior of blood parasitism of Cuckoo species. The main advantages of Cuckoo Search algorithm are its simplicity, less computational time and efficiency. With said advantages, a novel method on video watermarking using Cuckoo search algorithm in DWT-SVD transform domain is proposed. SSIM, BER are used for fitness function in optimization function. The method proposed uses secret share method to achieve more security of watermark. The experimental results prove that the proposed video watermarking method provides good imperceptibility and more robust to attacks compared to few related methods

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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