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
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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
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Physics-informed machine learning and mechanistic modeling of additive manufacturing to reduce defects
TL;DR: In this paper, a combination of physics-informed machine learning, mechanistic modeling, and experimental data is used to reduce the occurrence of common defects in additive manufacturing, such as balling, cracking, lack of fusion, porosity, and surface roughness.
Journal ArticleDOI
Advances of metaheuristic algorithms in training neural networks for industrial applications
TL;DR: This article tries to compare and summarize the properties of various metaheuristic algorithms in terms of their convergence rate and the ability to avoid the local minima and categorizes the latest meta heuristic search algorithm in the literature to indicate their efficiency in training ANN for various industry applications.
Journal ArticleDOI
Optimization strategies of neural networks for impact damage classification of RC panels in a small dataset
TL;DR: In this paper, a stepwise grid search (SG) method was incorporated into a nested cross-validation (NCV) process to find the optimal parameters for the ANN model, named SG-NCV-ANN.
Journal ArticleDOI
Sensitivity analysis of drill wear and optimization using Adaptive Neuro fuzzy –genetic algorithm technique toward sustainable machining
Lip Huat Saw,Li Wen Ho,Ming Chian Yew,Farazila Yusof,Nugroho Agung Pambudi,Tan Ching Ng,Ming Kun Yew +6 more
TL;DR: In this article, the influence of different drilling parameters on average drilling torque and thrust force were determined through Adaptive Neuro Fuzzy Inference System (ANFIS) and genetic algorithm (GA) was used to identify the optimal drilling parameter for different diameters of drill.
Journal ArticleDOI
Application of Polycrystalline SnO2 Sensor Chromatographic System to Detect Dissolved Gases in Transformer Oil
TL;DR: In this article, a wavelet-genetic algorithm (GA) threshold denoising method is proposed for noise reduction and applied to chromatogram to detect the weak peaks of the PGCD for latent transformer faults.
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).
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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.