Implementation of meta-heuristic optimization algorithms for interview problem in land consolidation: A case study in Konya/Turkey

2021 ◽  
Vol 108 ◽  
pp. 105511
Author(s):  
Sifa Ozsari ◽  
Harun Uguz ◽  
Huseyin Hakli
Keyword(s):  
Optimization Algorithms ◽  
Land Consolidation ◽  
Heuristic Optimization

Short to Long-Term Forecasting of River Flows by Heuristic Optimization Algorithms Hybridized with ANFIS

2021 ◽  
Vol 35 (4) ◽  
pp. 1149-1166
Author(s):  
Hossien Riahi-Madvar ◽  
Majid Dehghani ◽  
Rasoul Memarzadeh ◽  
Bahram Gharabaghi
Keyword(s):  
Optimization Algorithms ◽  
Heuristic Optimization ◽  
River Flows ◽  
Long Term Forecasting

scholarly journals Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3385
Author(s):  
Erickson Puchta ◽  
Priscilla Bassetto ◽  
Lucas Biuk ◽  
Marco Itaborahy Filho ◽  
Attilio Converti ◽  
...  
Keyword(s):  
Pid Controller ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Buck Converter ◽  
Algebraic Solution ◽  
Nonlinear Load ◽  
Bee Colony ◽  
Arduous Task ◽  
Whale Optimization

This work deals with metaheuristic optimization algorithms to derive the best parameters for the Gaussian Adaptive PID controller. This controller represents a multimodal problem, where several distinct solutions can achieve similar best performances, and metaheuristics optimization algorithms can behave differently during the optimization process. Finding the correct proportionality between the parameters is an arduous task that often does not have an algebraic solution. The Gaussian functions of each control action have three parameters, resulting in a total of nine parameters to be defined. In this work, we investigate three bio-inspired optimization methods dealing with this problem: Particle Swarm Optimization (PSO), the Artificial Bee Colony (ABC) algorithm, and the Whale Optimization Algorithm (WOA). The computational results considering the Buck converter with a resistive and a nonlinear load as a case study demonstrated that the methods were capable of solving the task. The results are presented and compared, and PSO achieved the best results.

scholarly journals Heuristic optimization of clusters of heat pumps: A simulation and case study of residential frequency reserve

2019 ◽  
Vol 233-234 ◽  
pp. 943-958 ◽  
Author(s):  
Laura Romero Rodríguez ◽  
Marcus Brennenstuhl ◽  
Malcolm Yadack ◽  
Pirmin Boch ◽  
Ursula Eicker
Keyword(s):  
Heat Pumps ◽  
Heuristic Optimization

scholarly journals DEVELOPING AGENT BASED HEURISTIC OPTIMISATION SYSTEM FOR COMPLEX FLOW SHOPS WITH CUSTOMER-IMPOSED PRODUCTION DISRUPTIONS

2018 ◽  
Author(s):  
Tunde Victor Adediran ◽  
Ammar Al-Bazi
Keyword(s):  
Research Work ◽  
Heuristic Optimization ◽  
Delivery Time ◽  
Complex Flow ◽  
Flow Shops ◽  
Agent Based ◽  
Equipment Manufacturer ◽  
Automotive Parts ◽  
Adaptive Framework

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies.  

scholarly journals LAND CONSOLIDATION AND IRRIGATION, CASE STUDY, MUNICIPALITY OF VELIKA PLANA

2016 ◽  
Vol 1 (14) ◽  
Author(s):  
Milan Trifković ◽  
Goran Marinković ◽  
Boban Ilić ◽  
Goran Pejičić ◽  
Jelena Lazić
Keyword(s):  
River Basin ◽  
Water Regime ◽  
Land Reclamation ◽  
Land Consolidation ◽  
Annual Basis ◽  
Hydrographic Features ◽  
Morava River ◽  
Morava River Basin

The Municipality of Velika Plana has been taking serious steps when it comes to initiating landconsolidation projects which help realize the land reclamation projects in the simplest way. Whit theaim of obtaining the base for carrying out land reclamation projects, this work deals with and presentsthe survey of the hydrographic features of Municipality of Velika Plana, as well as, water regime andthe river basin of the Velika Morava River. Based on measuring data obtained at Ljubicevski most,water gauge survey station we have performed and presented the analysis of the distinctive annual flowover a longer period of time as well as the analysis related to the changes in parameters which occur onan annual basis. On the basis of performed analysis we have been able to determine the amounts ofwater for irrigation available in the Velika Morava River basin at the territory of Velika Plana, whichwas the main focus and objective of this research.

The suitability and sustainability of governance structures in land consolidation under institutional change: A comparative case study

2021 ◽  
Vol 87 ◽  
pp. 276-291
Author(s):  
Xiaobin Zhang ◽  
Walter Timo de Vries ◽  
Guan Li ◽  
Yanmei Ye ◽  
Linlin Zhang ◽  
...  
Keyword(s):  
Institutional Change ◽  
Land Consolidation ◽  
Comparative Case Study ◽  
Governance Structures

VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh)

2018 ◽  
Vol 18 (51) ◽  
pp. 183-198
Author(s):  
masooume darmani ◽  
Mohammad Nahtani ◽  
haedeh Ara ◽  
Ali Golkarian ◽  
Salman Sharif Azari ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Design ◽  
Optimization Algorithms

Py_FS: A Python Package for Feature Selection Using Meta-Heuristic Optimization Algorithms

2021 ◽  
pp. 495-504
Author(s):  
Ritam Guha ◽  
Bitanu Chatterjee ◽  
S. K. Khalid Hassan ◽  
Shameem Ahmed ◽  
Trinav Bhattacharyya ◽  
...  
Keyword(s):  
Feature Selection ◽  
Optimization Algorithms ◽  
Heuristic Optimization ◽  
Python Package

Application of Meta-Heuristic Optimization Algorithms in Electric Power Systems

2015 ◽  
pp. 1292-1341
Author(s):  
N.I. Voropai ◽  
A. Z. Gamm ◽  
A. M. Glazunova ◽  
P. V. Etingov ◽  
I. N. Kolosok ◽  
...  
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Optimization Algorithms ◽  
Main Tool ◽  
Electric Power Systems ◽  
Heuristic Optimization ◽  
State Variables ◽  
State Equations ◽  
Electric Power Supply ◽  
Linear And Nonlinear Programming

Optimization of solutions on expansion of electric power systems (EPS) and their control plays a crucial part in ensuring efficiency of the power industry, reliability of electric power supply to consumers and power quality. Until recently, this goal was accomplished by applying classical and modern methods of linear and nonlinear programming. In some complicated cases, however, these methods turn out to be rather inefficient. Meta-heuristic optimization algorithms often make it possible to successfully cope with arising difficulties. State estimation (SE) is used to calculate current operating conditions of EPS using the SCADA measurements of state variables (voltages, currents etc.). To solve the SE problem, the Energy Systems Institute of Siberian Branch of Russian Academy of Sciences (ESI of SB RAS) has devised a method based on test equations (TE), i.e. on the steady state equations that contain only measured parameters. Here, a technique for EPS SE using genetic algorithms (GA) is suggested. SE is the main tool for EPS monitoring. The quality of SE results determines largely the EPS control efficiency. An algorithm for exclusion of wrong SE calculations is described. The algorithm using artificial neural networks (ANN) is based on the analysis of results of the calculation performed solving the SE problem with different combinations of constants. The proposed procedure is checked on real data.

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