scholarly journals Hybrid Optimization Approach for the Design of Mechanisms Using a New Error Estimator

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
A. Sedano ◽  
R. Sancibrian ◽  
A. de Juan ◽  
F. Viadero ◽  
F. Egaña
Keyword(s):  
Evolutionary Algorithm ◽  
Optimization Technique ◽  
Hybrid Optimization ◽  
Error Estimator ◽  
Optimization Approach ◽  
Deterministic Approach ◽  
Dimensional Synthesis ◽  
Fitness Evaluation ◽  
Variable Space ◽  
Two Stages

A hybrid optimization approach for the design of linkages is presented. The method is applied to the dimensional synthesis of mechanism and combines the merits of both stochastic and deterministic optimization. The stochastic optimization approach is based on a real-valued evolutionary algorithm (EA) and is used for extensive exploration of the design variable space when searching for the best linkage. The deterministic approach uses a local optimization technique to improve the efficiency by reducing the high CPU time that EA techniques require in this kind of applications. To that end, the deterministic approach is implemented in the evolutionary algorithm in two stages. The first stage is the fitness evaluation where the deterministic approach is used to obtain an effective new error estimator. In the second stage the deterministic approach refines the solution provided by the evolutionary part of the algorithm. The new error estimator enables the evaluation of the different individuals in each generation, avoiding the removal of well-adapted linkages that other methods would not detect. The efficiency, robustness, and accuracy of the proposed method are tested for the design of a mechanism in two examples.

scholarly journals Hybrid optimization design approach of asymmetric base-isolation coupling system for twin buildings

2021 ◽  
pp. 146134842199296
Author(s):  
Wonsuk Park ◽  
Seung-Yong Ok
Keyword(s):  
Vibration Control ◽  
Optimization Design ◽  
Base Isolation ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Efficient Design ◽  
Coupling System ◽  
Twin Buildings

This study proposes a new configuration of asymmetric base-isolation coupling system for the vibration control of twin buildings, and also presents an efficient design method of using a hybrid optimization technique integrated with preference-based dimensionality reduction technique. The purpose of the proposed optimization approach is to guarantee the compromise optimal solution of well-balancing the mutually conflicting design objectives. In order to demonstrate the proposed approach, the adjacent 20-story twin buildings subjected to earthquake excitations were adopted as target buildings and it was verified through numerical examples that the proposed optimization technique can successfully find the optimal solution to achieve various design objectives in a balanced manner. The seismic performance was also compared with the existing different-story connection system with uniform distribution of dampers. The comparative results of the seismic performances between two systems clearly demonstrate that the proposed system can achieve great performance improvement over the existing system while maintaining balanced design preferences. Thus, it can be concluded that the proposed system can be a very effective system for the vibration control problem of the twin buildings.

scholarly journals A Hybrid Optimization Approach for the Enhancement of Efficiency of a Piezoelectric Energy Harvesting System

Electronics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 75
Author(s):  
Mahidur R. Sarker ◽  
Ramizi Mohamed ◽  
Mohamad Hanif Md Saad ◽  
Muhammad Tahir ◽  
Aini Hussain ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Power Loss ◽  
Power Efficiency ◽  
Optimization Technique ◽  
Optimization Method ◽  
Hybrid Optimization ◽  
Piezoelectric Energy Harvesting ◽  
Optimization Approach ◽  
Piezoelectric Energy ◽  
Energy Harvesting System

This paper presents a hybrid optimization approach for the enhancement of performance of a piezoelectric energy harvesting system (PEHS). The existing PEHS shows substantial power loss during hardware implementation. To overcome the problem, this study proposes a hybrid optimization technique to improve the PEHS efficiency. In addition, the converter design as well as controller technique are enhanced and simulated in a MATLAB/Simulink platform. The controller technique of the proposed structure is connected to the converter prototype through the dSPACE DS1104 board (dSPACE, Paderborn, Germany). To enhance the proportional-integral voltage controller (PIVC) based on hybrid optimization method, a massive enhancement in reducing the output error is done in terms of power efficiency, power loss, rising time and settling time. The results show that the overall PEHS converter efficiency is about 85% based on the simulation and experimental implementations.

A Joint Multicast Optimization Approach for QoS Provisioning in Optical Label Switching (OLS) Networks

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Yassine Khlifi ◽  
Majid Alotaibi
Keyword(s):  
Traffic Management ◽  
Network Performance ◽  
Data Transfer ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Wavelength Converter ◽  
Label Switching ◽  
Link Capacity ◽  
Two Stages ◽  
Logical Topology

AbstractOptical label switching is introduced for ensuring fast data transfer, quality of service (QoS) support, and better resource management. However, the important issue is how to optimize resource usage and satisfy traffic constraints for improving network performance and design. This paper proposes a dynamic approach that optimizes the resource in terms of link capacity and FDL (fiber delay line) buffering as well as a wavelength converter. The proposed approach decreases the resources usage and guarantees QoS support for various traffic demands. The optimization strategy consists of two stages: path building and traffic management. The path building assures logical topology making using the cumulative cost of available resource and traffic requirements including unicast and multicast. The traffic management solves the resource formulation problem during the traffic transfer by guaranteeing the required loss and blocking delay. Simulation work is conducted for validating the proposed approach and evaluating its performances and effectiveness. Simulation results show that our proposal minimizes effectively the use of link capacity of lightpath and light-tree. Moreover, our approach optimizes the use of buffering capacity and wavelength converter and guarantees QoS support according to traffic requirements.

A hybrid optimization approach in non-isothermal glass molding

2016 ◽  
Author(s):  
Anh-Tuan Vu ◽  
Holger Kreilkamp ◽  
Bharathwaj Janaki Krishnamoorthi ◽  
Olaf Dambon ◽  
Fritz Klocke
Keyword(s):  
Hybrid Optimization ◽  
Optimization Approach ◽  
Glass Molding

Co-Evolutionary Algorithm between Helicopter and Submarine

2015 ◽  
Vol 719-720 ◽  
pp. 1229-1235
Author(s):  
Ying Chun Chen ◽  
Xian Hua Wang
Keyword(s):  
Evolutionary Algorithm ◽  
Optimal Strategy ◽  
Theoretical Foundation ◽  
Optimal Strategies ◽  
Evaluation Methods ◽  
Movement Model ◽  
Fitness Evaluation ◽  
Detection Model ◽  
Ocean Environment

A co-evolutionary algorithm is proposed for the play between a submarine and a helicopter equipped with dipping sonar. First, the theoretical foundation of co-evolution is elaborated. The movement model of helicopter and submarine, the detection model of dipping sonar under certain ocean environment are established. After defining the strategies of helicopter and submarine and fitness evaluation methods, the process of co-evolutionary algorithm is described. The optimal strategy of helicopter after helicopter evolution, and the optimal strategies of both helicopter and submarine after co-evolution are given

HYBRIDIZATION OF MULTIOBJECTIVE EVOLUTIONARY ALGORITHM WITH COEVOLUTION FOR ENEMY TEAM IN MS. PAC-MAN GAME

2014 ◽  
Vol 2 (1) ◽  
pp. 36-51
Author(s):  
Tse guan Tan ◽  
Jason Teo ◽  
On Chin Kim
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Multiobjective Optimization ◽  
Evolutionary Algorithm ◽  
Optimization Technique ◽  
Dynamic Game ◽  
Evolution Strategy ◽  
Evolutionary Multiobjective Optimization ◽  
Competitive Coevolution ◽  
Virtual Creatures

AbstrakKini, semakin ramai penyelidik telah menunjukkan minat mengkaji permainan Kecerdasan Buatan (KB).Permainan seumpama ini menyediakan tapak uji yang sangat berguna dan baik untuk mengkaji asasdan teknik-teknik KB. Teknik KB, seperti pembelajaran, pencarian dan perencanaan digunakan untukmenghasilkan agen maya yang mampu berfikir dan bertindak sewajarnya dalam persekitaran permainanyang kompleks dan dinamik. Dalam kajian ini, satu set pengawal permainan autonomi untuk pasukan hantudalam permainan Ms. Pac-man yang dicipta dengan menggunakan penghibridan Evolusi PengoptimumanMultiobjektif (EPM) dan ko-evolusi persaingan untuk menyelesaikan masalah pengoptimuman dua objektifiaitu meminimumkan mata dalam permainan dan bilangan neuron tersembunyi di dalam rangkaianneural buatan secara serentak. Arkib Pareto Evolusi Strategi (APES) digunakan, teknik pengoptimumanmultiobjektif ini telah dibuktikan secara saintifik antara yang efektif di dalam pelbagai aplikasi. Secarakeseluruhannya, keputusan eksperimen menunjukkan bahawa teknik pengoptimuman multiobjektif bolehmendapat manfaat daripada aplikasi ko-evolusi persaingan Abstract Recently, researchers have shown an increased interest in game Artificial Intelligence (AI). Gamesprovide a very useful and excellent testbed for fundamental AI research. The AI techniques, such aslearning, searching and planning are applied to generate the virtual creatures that are able to think andact appropriately in the complex and dynamic game environments. In this study, a set of autonomousgame controllers for the ghost team in the Ms. Pac-man game are created by using the hybridizationof Evolutionary Multiobjective Optimization (EMO) and competitive coevolution to solve the bi-objectiveoptimization problem of minimizing the game's score by eating Ms. Pac-man agent and the number ofhidden neurons in neural network simultaneously. The Pareto Archived Evolution Strategy (PAES) is usedthat has been proved to be an effective and efficient multiobjective optimization technique in variousapplications. Overall, the results show that multiobjective optimizer can benefit from the application ofcompetitive coevolutionary

Distribution Network Reconfiguration Using an Approximate Optimization Approach

2013 ◽  
Vol 303-306 ◽  
pp. 1276-1279
Author(s):  
Hai Na Rong ◽  
Yan Hui Qin
Keyword(s):  
Evolutionary Algorithm ◽  
Distribution Network ◽  
Operating Conditions ◽  
Distribution Automation ◽  
Optimization Approach ◽  
Network Reconfiguration ◽  
Power Network ◽  
Distribution Network Reconfiguration ◽  
Service Restoration ◽  
Integer Programming Problems

Power network reconfiguration is an important process in the improvement of operating conditions of a power system and in planning studies, service restoration and distribution automation when remote-controlled switches are employed. This paper presents the use of a quantum-inspired evolutionary algorithm to solve the distribution network reconfiguration problem. The quantum- inspired evolutionary algorithm is the combination product of quantum computing and evolutionary computation and is suitable for a class of integer programming problems such as the distribution network reconfiguration problem. After the analysis and formulation of the distribution network reconfiguration problem, the effectiveness and feasibility of the introduced method is verified by a large number of experiments.

scholarly journals A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
C. Mallika ◽  
S. Selvamuthukumaran
Keyword(s):  
Predictive Accuracy ◽  
Optimization Technique ◽  
Hybrid Optimization ◽  
Support Vector ◽  
Grey Wolf Optimizer ◽  
Diagnostic Model ◽  
Full Potential ◽  
Diabetes Diagnosis ◽  
Grey Wolf ◽  
Diagnosis System

AbstractDiabetes is an extremely serious hazard to global health and its incidence is increasing vividly. In this paper, we develop an effective system to diagnose diabetes disease using a hybrid optimization-based Support Vector Machine (SVM).The proposed hybrid optimization technique integrates a Crow Search algorithm (CSA) and Binary Grey Wolf Optimizer (BGWO) for exploiting the full potential of SVM in the diabetes diagnosis system. The effectiveness of our proposed hybrid optimization-based SVM (hereafter called CS-BGWO-SVM) approach is carefully studied on the real-world databases such as UCIPima Indian standard dataset and the diabetes type dataset from the Data World repository. To evaluate the CS-BGWO-SVM technique, its performance is related to several state-of-the-arts approaches using SVM with respect to predictive accuracy, Intersection Over-Union (IoU), specificity, sensitivity, and the area under receiver operator characteristic curve (AUC). The outcomes of empirical analysis illustrate that CS-BGWO-SVM can be considered as a more efficient approach with outstanding classification accuracy. Furthermore, we perform the Wilcoxon statistical test to decide whether the proposed cohesive CS-BGWO-SVM approach offers a substantial enhancement in terms of performance measures or not. Consequently, we can conclude that CS-BGWO-SVM is the better diabetes diagnostic model as compared to modern diagnosis methods previously reported in the literature.

scholarly journals Energy management strategies for combined heat and electric power micro-grid

2016 ◽  
Vol 20 (4) ◽  
pp. 1091-1103 ◽  
Author(s):  
Marina Barbaric ◽  
Drazen Loncar
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Optimization Technique ◽  
Management Strategies ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Optimization Approach ◽  
Micro Grid ◽  
Additional Rule

The increasing energy production from variable renewable energy sources such as wind and solar has resulted in several challenges related to the system reliability and efficiency. In order to ensure the supply-demand balance under the conditions of higher variability the micro-grid concept of active distribution networks arising as a promising one. However, to achieve all the potential benefits that micro-gird concept offer, it is important to determine optimal operating strategies for micro-grids. The present paper compares three energy management strategies, aimed at ensuring economical micro-grid operation, to find a compromise between the complexity of strategy and its efficiency. The first strategy combines optimization technique and an additional rule while the second strategy is based on the pure optimization approach. The third strategy uses model based predictive control scheme to take into account uncertainties in renewable generation and energy consumption. In order to compare the strategies with respect to cost effectiveness, a residential micro-grid comprising photovoltaic modules, thermal energy storage system, thermal loads, electrical loads as well as combined heat and power plant, is considered.

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