scholarly journals The Nomadic People Optimizer applied to the economic dispatch problem with prohibited operating zones

2021 ◽  
Author(s):  
Lucas Santiago Nepomuceno ◽  
Gabriel Schreider Silva ◽  
Edimar Jose Oliveira ◽  
Arthur Neves Paula ◽  
Edmarcio Antonio Belati
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Prohibited Operating Zones ◽  
Whale Optimization ◽  
Nomadic People ◽  
Sensibility Analysis ◽  
Economic Dispatch Problem ◽  
Better Than

This work proposes the application of the Nomadic People Optimizer (NPO) to solve the economic dispatch problem considering Prohibitive Operating Zones (POZ). The NPO is a swarm-based metaheuristic recently introduced in the literature and still under-explored. In addition, the POZ increase the difficulties to find the optimal solution of the economic dispatch problem. The performance of the proposed methodology is compared with others metaheuristics present in the literature. Also, a sensibility analysis was performed. The NPO performed better than Ant Colony Optimization (ACO) and Whale Optimization Algorithm (WOA) metaheuristics in solving the problem.

scholarly journals Solving the Environmental Economic Dispatch Problem using Whale Optimization Algorithm

2017 ◽  
Vol 4 (1) ◽  
pp. 50-60
Author(s):  
Haider J.Touma
Keyword(s):  
Genetic Algorithm ◽  
Environmental Economic ◽  
Optimization Algorithm ◽  
Economic Dispatch ◽  
Test System ◽  
Standard Test ◽  
Whale Optimization Algorithm ◽  
Whale Optimization ◽  
Economic Dispatch Problem ◽  
Intelligent Methods

In this work, the Whale Optimization Algorithm method used to solve the Environmental Economic Dispatch Problem. The performance of the used algorithm is substantiated using standard test system of three thermal generating units. The proposed algorithm produced optimum or near optimum solutions. The obtained results in this study using the Whale Optimization Algorithm are compared with the obtained results using other intelligent methods such as Particle Swarm Optimization, Simple Genetic Algorithm and Genetic Algorithm. The comparison demonstrated the obtained results in this research are close to these obtained using the above revealed approaches.

scholarly journals Study of The Economic Dispatch Problem on IEEE 30-Bus System using Whale Optimization Algorithm

2016 ◽  
Vol 3 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Haider J. Touma
Keyword(s):  
Optimization Algorithm ◽  
Economic Dispatch ◽  
Test System ◽  
Standard Test ◽  
Whale Optimization Algorithm ◽  
Swarm Optimization ◽  
Whale Optimization ◽  
New Strategy ◽  
Economic Dispatch Problem ◽  
Intelligent Methods

This work presents one of the latest meta heuristic optimization approaches named Whale Optimization Algorithm method as a new strategy to solve the Economic Dispatch problem . The execution of the utilized algorithm is verified using standard test system of IEEE 30-Bus. The proposed algorithm delivered optimum or close optimum solutions. The achieved results in this study using the above mentioned Algorithm have been compared with the obtained results using other intelligent methods such as Particle Swarm Optimization, Ant Colony optimization and Genetic Algorithm. The comparison explained the obtained results in this study are close to these obtained using the above revealed approaches.

Whale optimization algorithm based on lateral inhibition for image matching and vision-guided AUV docking

2020 ◽  
pp. 1-12
Author(s):  
Zheping Yan ◽  
Jinzhong Zhang ◽  
Jialing Tang
Keyword(s):  
Lateral Inhibition ◽  
Optimization Algorithm ◽  
Image Matching ◽  
Autonomous Underwater Vehicle ◽  
Optimal Solution ◽  
Search Space ◽  
Whale Optimization Algorithm ◽  
Inhibition Mechanism ◽  
Whale Optimization ◽  
Accuracy And Stability

The accuracy and stability of relative pose estimation of an autonomous underwater vehicle (AUV) and a target depend on whether the characteristics of the underwater image can be accurately and quickly extracted. In this paper, a whale optimization algorithm (WOA) based on lateral inhibition (LI) is proposed to solve the image matching and vision-guided AUV docking problem. The proposed method is named the LI-WOA. The WOA is motivated by the behavior of humpback whales, and it mainly imitates encircling prey, bubble-net attacking and searching for prey to obtain the globally optimal solution in the search space. The WOA not only balances exploration and exploitation but also has a faster convergence speed, higher calculation accuracy and stronger robustness than other approaches. The lateral inhibition mechanism can effectively perform image enhancement and image edge extraction to improve the accuracy and stability of image matching. The LI-WOA combines the optimization efficiency of the WOA and the matching accuracy of the LI mechanism to improve convergence accuracy and the correct matching rate. To verify its effectiveness and feasibility, the WOA is compared with other algorithms by maximizing the similarity between the original image and the template image. The experimental results show that the LI-WOA has a better average value, a higher correct rate, less execution time and stronger robustness than other algorithms. The LI-WOA is an effective and stable method for solving the image matching and vision-guided AUV docking problem.

An Improved and Realized Volatility Strategy of the Ant Colony Optimization Algorithm

2013 ◽  
Vol 389 ◽  
pp. 849-853
Author(s):  
Fang Song Cui ◽  
Wei Feng ◽  
Da Zhi Pan ◽  
Guo Zhong Cheng ◽  
Shuang Yang
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Ant Colony ◽  
Ant System ◽  
Ant Colony Optimization Algorithm ◽  
Volatility Model ◽  
Local Optimal Solution ◽  
The Impact ◽  
Improved Algorithm

In order to overcome the shortcomings of precocity and stagnation in ant colony optimization algorithm, an improved algorithm is presented. Considering the impact that the distance between cities on volatility coefficient, this study presents an model of adjusting volatility coefficient called Volatility Model based on ant colony optimization (ACO) and Max-Min ant system. There are simulation experiments about TSP cases in TSPLIB, the results show that the improved algorithm effectively overcomes the shortcoming of easily getting an local optimal solution, and the average solutions are superior to ACO and Max-Min ant system.

scholarly journals An Improved Whale Algorithm for Setting Standard Scheduled Block Time Based on the Airline Fairness

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qian Wang ◽  
Yong Tian ◽  
Lili Lin ◽  
Ratnaji Vanga ◽  
Lina Ma
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Optimization Algorithm ◽  
Whale Optimization Algorithm ◽  
Civil Aviation ◽  
Convergence Factor ◽  
Suggested Approach ◽  
Whale Optimization ◽  
Block Time ◽  
Better Than

Standard scheduled flight block time (SBT) setting is of great concern for Civil Aviation Administration of China (CAAC) and airlines in China. However, the standard scheduled flight block times are set in the form of on-site meetings in practice and current literature has not provided any efficient mathematical models to calculate the flight block times fairly among the airlines. The objective of this paper is to develop and solve a mathematical model for standard SBT setting with consideration of both fairness and reliability. We use whale optimization algorithm (WOA) and an improved version of the whale optimization algorithm (IWOA) to solve the SBT setting problem. A novel nonlinear update equation of convergence factor for random iterations is used in place of the original linear one in the proposed IWOA algorithm. Experimental results show that the suggested approach is effective, and IWOA performs better than WOA in the concerned problem, whose solutions are better compared to the flight block times released by CAAC. In particular, it is interesting to find that MSE, RMSE, MAE, MAPE and Theil of the reliability in 60%–70% range are always the smallest and the average fairness of airlines is better than that of 60%–75% range. The model and solving approach presented in this article have great potential to be applied by CAAC to determine the standard SBTs strategically.

scholarly journals Application of Whale Optimization Algorithm to Inverse Scattering of an Imperfect Conductor with Corners

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Kun-Chou Lee ◽  
Pai-Ting Lu
Keyword(s):  
Inverse Scattering ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Spline Interpolation ◽  
Optimal Solution ◽  
Whale Optimization Algorithm ◽  
Humpback Whales ◽  
Hunting Behavior ◽  
Whale Optimization ◽  
The Moment

In this paper, the whale optimization algorithm (WOA) is applied to the inverse scattering of an imperfect conductor with corners. The WOA is a new metaheuristic optimization algorithm. It mimics the hunting behavior of humpback whales. The inspiration results from the fact that a whale recognizes the location of a prey (i.e., optimal solution) by swimming around the prey within a shrinking circle and along a spiral-shaped path simultaneously. Initially, the inverse scattering is first transformed into a nonlinear optimization problem. The transformation is based on the moment method solution for scattering integral equations. To treat a target with corners and implement the WOA inverse scattering, the cubic spline interpolation is utilized for modelling the target shape function. Numerical simulation shows that the inverse scattering by WOA not only is accurate but also converges fast.

Crisscross optimization algorithm for large-scale dynamic economic dispatch problem with valve-point effects

Energy ◽  
2015 ◽  
Vol 93 ◽  
pp. 2175-2190 ◽  
Author(s):  
Anbo Meng ◽  
Hanwu Hu ◽  
Hao Yin ◽  
Xiangang Peng ◽  
Zhuangzhi Guo
Keyword(s):  
Optimization Algorithm ◽  
Large Scale ◽  
Economic Dispatch ◽  
Economic Dispatch Problem ◽  
Dynamic Economic Dispatch
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