Journal ArticleDOI
Genetic Algorithm and its Applications to Mechanical Engineering: A Review
Trupti Bhoskar,Omkar Kulkarni,Ninad Kulkarni,Sujata Patekar,Ganesh Kakandikar,Vilas M. Nandedkar +5 more
TLDR
Genetic algorithm is a multi-path algorithm that searches many peaks in parallel, hence reducing the possibility of local minimum trapping and solve the multi-objective optimization problems.About:
This article is published in Materials Today: Proceedings.The article was published on 2015-01-01. It has received 82 citations till now. The article focuses on the topics: Meta-optimization & Genetic representation.read more
Citations
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Journal ArticleDOI
Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures
Devin J. Roach,Devin J. Roach,Andrew Rohskopf,Craig M. Hamel,William Reinholtz,Robert Bernstein,H. Jerry Qi,Adam Cook +7 more
TL;DR: In this article, an artificial neural network (ANN) was trained and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image.
Optimal Power Dispatch of DGs in DC Power Grids: a Hybrid Gauss-Seidel-Genetic-Algorithm Methodology for Solving the OPF Problem
TL;DR: Genetic-Algorithm proposed in this paper corresponds to a continuous variant of the conventional binary approaches and shows the efficiency and accuracy when is compared to GAMS/CONOPT nonlinear solver.
Journal ArticleDOI
An Accurate PSO-GA Based Neural Network to Model Growth of Carbon Nanotubes
TL;DR: The results show that PSOGANN can be successfully utilized for modeling the experimental parameters that are critical for the growth of CNTs.
Journal ArticleDOI
Adaptive stochastic resonance quantified by a novel evaluation index for rotating machinery fault diagnosis
Yan Lin,Xing'ang Xu,Chao Ye +2 more
TL;DR: A weighted impulse (WI) index is proposed to evaluate the performance of the adaptive general scale transformation SR (AGSTSR) in rotating machinery fault diagnosis and an intelligent optimization algorithm is used to obtain the optimal WI.
Journal ArticleDOI
Implementation and Identification of Preisach Parameters: Comparison Between Genetic Algorithm, Particle Swarm Optimization, and Levenberg–Marquardt Algorithm
TL;DR: The LM method is the most suitable technique for the identification of Preisach hysteresis model combined with the Lorentz modified distribution function to describe the magnetic behavior of a fully processed nonoriented Fe–3wt% Si steel sheet under static excitation.
References
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Journal ArticleDOI
A general heuristic for vehicle routing problems
David Pisinger,Stefan Ropke +1 more
TL;DR: A unified heuristic which is able to solve five different variants of the vehicle routing problem and shown promising results for a large class of vehicle routing problems with backhauls as demonstrated in Ropke and Pisinger.
Dissertation
A genetic algorithm for resource-constrained scheduling
TL;DR: Jakiela et al. as discussed by the authors presented a genetic algorithm approach to resource-constrained scheduling using a direct, time-based representation, which was applied to over 1000 small job shop and project scheduling problems (10-300 activities, 3-10 resource types).
Journal ArticleDOI
A genetic local search algorithm for minimizing total weighted tardiness in the job-shop scheduling problem
TL;DR: This paper considers the job-shop problem with release dates and due dates with the objective of minimizing the total weighted tardiness, and shows that the efficiency of genetic algorithms does no longer depend on the schedule builder when an iterated local search is used.
Journal ArticleDOI
Genetic algorithm-based optimization of cutting parameters in turning processes
Doriana M. D’Addona,Roberto Teti +1 more
TL;DR: An optimization paradigm based on GA for the determination of the cutting parameters in machining operations is proposed in this article, where the GA has been used as an optimal solution finder for finding optimal cutting parameters during a turning process.
Journal ArticleDOI
Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm
TL;DR: In this article, different scheduling mechanisms are designed to generate optimum scheduling; these include non-traditional approaches such as genetic algorithm (GA), simulated annealing (SA) algorithm, memetic algorithm (MA) and particle swarm algorithm (PSA) by considering multiple objectives.