Object-Oriented Optimization Approach Using Genetic Algorithms for Lattice Towers

2004 ◽  
Vol 18 (2) ◽  
pp. 162-171 ◽  
Author(s):  
P. Sivakumar ◽  
A. Rajaraman ◽  
G. M. Samuel Knight ◽  
D. S. Ramachandramurthy
Keyword(s):  
Genetic Algorithms ◽  
Object Oriented ◽  
Optimization Approach ◽  
Lattice Towers

scholarly journals KPLS optimization approach using genetic algorithms

2020 ◽  
Vol 170 ◽  
pp. 1153-1160 ◽  
Author(s):  
Jorge Daniel Mello-Román ◽  
Adolfo Hernandez
Keyword(s):  
Genetic Algorithms ◽  
Optimization Approach

scholarly journals Read-across predictions of nanoparticle hazard endpoints: a mathematical optimization approach

2019 ◽  
Vol 1 (9) ◽  
pp. 3485-3498 ◽  
Author(s):  
Dimitra-Danai Varsou ◽  
Antreas Afantitis ◽  
Georgia Melagraki ◽  
Haralambos Sarimveis
Keyword(s):  
Genetic Algorithms ◽  
Mathematical Optimization ◽  
Optimization Approach

Development of a novel read-across methodology for the prediction of toxicity related endpoints of nanoparticles based on genetic algorithms.

A Analysis and Research on the Methods of Object Oriented Software Testing

2013 ◽  
Vol 709 ◽  
pp. 616-619
Author(s):  
Jing Chen
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Test Data ◽  
Object Oriented ◽  
Automatic Generation ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Path Coverage ◽  
Parameter Values

This paper proposes a genetic algorithm-based method to generate test cases. This method provides information for test case generation using state machine diagrams. Its feature is realizing automation through fewer generated test cases. In terms of automatic generation of test data based on path coverage, the goal is to build a function that can excellently assess the generated test data and guide the genetic algorithms to find the targeting parameter values.

scholarly journals Design of low-power CMOS VLSI circuits using multi-objective optimization in genetic algorithms

2021 ◽  
Vol 12 (1) ◽  
pp. 215-224
Author(s):  
Mahnoor Maghroori ◽  
Mehdi Dolatshahi
Keyword(s):  
Genetic Algorithms ◽  
Integrated Circuits ◽  
Circuit Simulation ◽  
Cmos Technology ◽  
Vlsi Circuits ◽  
Design Tool ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cmos Vlsi

This paper presents a design CAD tool for automated design of digital CMOS VLSI circuits. In order to fit the circuit performance into desired specifications, a multi-objective optimization approach based on genetic algorithms (GA) is proposed and the transistor sizes are calculated based on the analytical equations describing the behavior of the circuit. The optimization algorithm is developed in MATLAB and the performance of the designed circuit is verified using HSPICE simulations based on 0.18µm CMOS technology parameters. Different digital integrated circuits were successfully designed and verified using the proposed design tool. It is also shown in this paper that, the design results obtained from the proposed algorithm in MATLAB, have a very good agreement with the obtained circuit simulation results in HSPICE.

Object-oriented job-shop scheduling using genetic algorithms

1997 ◽  
Vol 32 (3) ◽  
pp. 281-294 ◽  
Author(s):  
F. Maturana ◽  
P. Gu ◽  
A. Naumann ◽  
D.H. Norrie
Keyword(s):  
Genetic Algorithms ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Object Oriented ◽  
Shop Scheduling
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