In an organization, a group of people working for a common goal may not achieve their goal unless they organize themselves in a hierarchy called Corporate Rank Hierarchy (CRH). This principle motivates us to map the concept of CRH to propose a new algorithm for optimization that logically arranges the search agents in a hierarchy based on their fitness. The proposed algorithm is named as heap-based optimizer (HBO) because it utilizes the heap data structure to map the concept of CRH. The mathematical model of HBO is built on three pillars: the interaction between the subordinates and their immediate boss, the interaction between the colleagues, and self-contribution of the employees. The proposed algorithm is benchmarked with 97 diverse test functions including 29 CEC-BC-2017 functions with very challenging landscapes against 7 highly-cited optimization algorithms including the winner of CEC-BC-2017 (EBO-CMAR). In the first two experiments, the exploitative and explorative behavior of HBO is evaluated by using 24 unimodal and 44 multimodal functions, respectively. It is shown through experiments and Friedman mean rank test that HBO outperforms and secures 1 st rank. In the third experiment, we use 29 CEC-BC-2017 benchmark functions. According to Friedman mean rank test HBO attains 2 nd position after EBO-CMAR; however, the difference in ranks of HBO and EBO-CMAR is shown to be statistically insignificant by using Bonferroni method based multiple comparison test. Moreover, it is shown through the Friedman test that the overall rank of HBO is 1 st for all 97 benchmarks. In the fourth and the last experiment, the applicability on real-world problems is demonstrated by solving 3 constrained mechanical engineering optimization problems. The performance is shown to be superior or equivalent to the other algorithms, which have been used in the literature. The source code of HBO is publicly available at https://github.com/qamar-askari/HBO.

Heap-based optimizer inspired by corporate rank hierarchy for global optimization

One of the most dangerous cancers in humans is Melanoma. However, early detection of melanoma can help us to cure it completely. This paper presents a new efficient method to detect malignancy in melanoma via images. At first, the extra scales are eliminated by using edge detection and smoothing. Afterwards, the proposed method can be utilized to segment the cancer images. Finally, the extra information is eliminated by morphological operations and used to focus on the area which melanoma boundary potentially exists. To do this, World Cup Optimization algorithm is utilized to optimize an MLP neural Networks (ANN). World Cup Optimization algorithm is a new meta-heuristic algorithm which is recently presented and has a good performance in some optimization problems. WCO is a derivative-free, Meta-Heuristic algorithm, mimicking the world's FIFA competitions. World cup Optimization algorithm is a global search algorithm while gradient-based back propagation method is local search. In this proposed algorithm, multi-layer perceptron network (MLP) employs the problem's constraints and WCO algorithm attempts to minimize the root mean square error. Experimental results show that the proposed method can develop the performance of the standard MLP algorithm significantly.

A Hybrid Neural Network - World Cup Optimization Algorithm for Melanoma Detection.

This paper proposes a novel tuning design of proportional integral derivative (PID) controller via an improved kidney-inspired algorithm (IKA) with a new objective function. The main objective of the proposed approach is to optimize the transient response of the AVR system by minimizing the maximum overshoot, settling time, rise time and peak time values of the terminal voltage, and eliminating the steady state error. After obtaining the optimal values of the three gains of the PID controller (KP, KI, and KD) with the proposed approach, the transient response analysis was performed and compared with some of the current heuristic algorithms-based approaches in literature to show the superiority of the optimized PID controller. In order to evaluate the stability of the automatic voltage regulator (AVR) system tuned by IKA method, the pole/zero map analysis and Bode analysis are performed. Finally, the robustness analysis of the proposed approach has been carried out with variations in the parameters of the AVR system. The numerical simulation results demonstrated that the proposed IKA tuned PID controller has better control performances compared to the other existing approaches. The essence of the presented study points out that the proposed approach may successfully be applied for the AVR system.

/pdf/improved-kidney-inspired-algorithm-approach-for-tuning-of-4dr9zmzdrs.pdf

Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System

https://www.econstor.eu/bitstream/10419/243697/1/1683642686.pdf

Experimental modeling of PEM fuel cells using a new improved seagull optimization algorithm

Dealing with categorical and integer-valued variables in Bayesian Optimization with Gaussian processes

This paper presents a new optimization algorithm based on human society’s intelligent contests. FIFA World Cup is an international association football competition competed by the senior men’s national teams. This contest is one of the most significant competitions among the humans in which people/teams try hard to overcome the others to earn the victory. In this competition there is only one winner which has the best position rather than the others. This paper introduces a new technique for optimization of mathematic functions based on FIFA World Cup competitions. The main difficulty of the optimization problems is that each type of them can be interpreted in a specific manner. World Cup Optimization (WCO) algorithm has a number of parameters to solve any type of problems due to defined parameters. For analyzing the system performance, it is applied on some benchmark functions. It is also applied on an optimal control problem as a practical case study to find the optimal parameters of PID controller with considering to the nominal operating points $$(K_{g}$$
 , $$T_{g})$$
 changes of the AVR system. The main objective of the proposed system is to minimize the steady-state error and also to improve the transient response of the AVR system by optimal PID controller. Optimal values of the PID controller which are achieved by WCO algorithm are then compared with particle swarm optimization and imperialist competitive algorithm in different situations. Finally for illustrating the system capability against the disturbance, it is applied on a generator with disturbance on it and the results are compared by the other algorithms. The simulation results show the excellence of WCO algorithm performance into the nature base and other competitive algorithms.

A New Meta-Heuristic Optimization Algorithm Inspired by FIFA World Cup Competitions: Theory and Its Application in PID Designing for AVR System

Nowadays, automatic generation control (AGC) is a very impressive problem in restructured power system operation for providing electric power with high quality and reliability. In this paper, the three-area multi-units system has been selected for AGC in a restructured power system. Federal energy regulatory commission supports an open market system for price-based operation. The theory of DISCO participation matrix is used to simulate the bilateral contracts in the three-area multi-units systems. In a restructured system because of open market system the power flow between areas is varying continuously however the system must be able to maintain stability in all conditions. In this paper, two cases for design robust controller have been considered. A new method using the imperialist competitive algorithm for designing this controller has been used. Finally, the obtained results are compared with other methods.

Design Robust Controller for Automatic Generation Control in Restructured Power System by Imperialist Competitive Algorithm

Automatic selection of color models has a great significance for machine vision purposes like image segmentation, object recognition, etc. Typically, selection of a proper color model is a problem that can just solve by testing the models on the target one by one. To achieve a proper color model, in this article, we propose a new method which is shaped on the basis of clustering and relation among models. The proposed method is verified experimentally for two different images (in thresholding purpose). The experimental results show that this method has a suitable power for automatic purposes.

Automatic selection and fusion of color spaces for image thresholding

This paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (PID) controller in hydro-turbine generator governor for damping output frequency oscillations. In this research, we utilize a stochastic and optimal based PID controller to control frequency-response of the hydro turbine. The proposed algorithm is employed to design an optimal PID controller by adjusting the PID parameters. Here, the parameters of the PID controller are optimized by IWO Algorithm. For analyzing the proposed technique, the final results of IWO algorithm is compared with ABC algorithm. Simulation results showed that the proposed method has better performance in different load condition of power system.

http://www.ijissm.org/article_559198_9791e1040fd35e8b255ea32894484f14.pdf

A new design for PID controller by considering the operating points changes in Hydro-Turbine Connected to the equivalent network by using Invasive Weed Optimization (IWO) Algorithm

Gas turbines are increasingly spread throughout the world to provide mechanical and electrical power in consumer and industrial sections. To ensure an accurate control process temperature of gas turbine with no extortionary operator involvement, a proper controller is required. Load frequency control of gas turbine is also regulates the power flow between different areas while holding the frequency constant. The main idea in this study is to assemble these 2 controllers in a unit work; the area of robust control has grown to be one of the wealthy in terms of algorithms, design techniques, analytical tools and modifications. Several books and papers already exist on the topics of parameter estimation and adaptive control. In The proposed approach, a robust and evolutionary based Proportional, Integral, Derivative (PID) is utilized to control frequency-response and a robust evolutionary based Proportional, Integral (PI) is utilized to control temperature. The evolutionary algorithm is used to make an optimal Proportional-Integral-Derivative (PID) controller Tuning parameters. The new robust PID controller is compared with a normal classic controller (Ziegler-Nichols) designed by the method.

Mohsen Khalilpour

Papers

A New Meta-Heuristic Optimization Algorithm Inspired by FIFA World Cup Competitions: Theory and Its Application in PID Designing for AVR System

Design Robust Controller for Automatic Generation Control in Restructured Power System by Imperialist Competitive Algorithm

Automatic selection and fusion of color spaces for image thresholding

A new design for PID controller by considering the operating points changes in Hydro-Turbine Connected to the equivalent network by using Invasive Weed Optimization (IWO) Algorithm

Designing a Robust and Adaptive PID Controller for Gas Turbine Connected to the Generator