Nothing Special   »   [go: up one dir, main page]

Chen et al., 2009 - Google Patents

Economic statistical design of non-uniform sampling scheme X bar control charts under non-normality and Gamma shock using genetic algorithm

Chen et al., 2009

Document ID
17796805524687083986
Author
Chen F
Yeh C
Publication year
Publication venue
Expert Systems with Applications

External Links

Snippet

This paper presented an approach which simultaneously considered the properties of cost and quality based on the Burr distribution and the non-unifampling scheme. The objective was to determine three parameters, namely, sample size, sampling interval between …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0639Performance analysis
    • G06Q10/06393Score-carding, benchmarking or key performance indicator [KPI] analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/11Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/12Computer systems based on biological models using genetic models
    • G06N3/126Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00Indexing scheme relating to computer aided design [CAD]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism

Similar Documents

Publication Publication Date Title
Chen et al. Economic statistical design of non-uniform sampling scheme X bar control charts under non-normality and Gamma shock using genetic algorithm
Dey et al. Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment
Chou et al. Economic design of variable sampling intervals T2 control charts using genetic algorithms
Chen et al. Economic design of the VSSI X control charts for correlated data
Peng et al. Parallel machine scheduling models with fuzzy processing times
Frank Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory
Barton et al. Metamodel-based simulation optimization
Ahmadi et al. A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem
Chen et al. Artificial neural networks to classify mean shifts from multivariate χ2 chart signals
Das et al. A volume flexible economic production lot-sizing problem with imperfect quality and random machine failure in fuzzy-stochastic environment
Chih et al. Particle swarm optimization for the economic and economic statistical designs of the X control chart
Anzanello et al. Multicriteria variable selection for classification of production batches
Qian et al. A copula-based hybrid estimation of distribution algorithm for m-machine reentrant permutation flow-shop scheduling problem
Garcia-Lopez et al. An improved robust topology optimization approach using multiobjective evolutionary algorithms
Abbas et al. Phase II monitoring of linear profiles with random explanatory variable under Bayesian framework
Amiri et al. Multi-objective economic-statistical design of MEWMA control chart
Pandita et al. Stochastic multiobjective optimization on a budget: Application to multipass wire drawing with quantified uncertainties
Nafei et al. Smart TOPSIS: a neural Network-Driven TOPSIS with neutrosophic triplets for green Supplier selection in sustainable manufacturing
Ibidoja et al. Robust M-estimators and machine learning algorithms for improving the predictive accuracy of seaweed contaminated big data
Chou et al. Joint economic design of variable sampling intervals (x) and r charts using genetic algorithms
Wang et al. Economic design under gamma shock model of the control chart for sustainable operations
Xu et al. A cluster prediction strategy with the induced mutation for dynamic multi-objective optimization
Singh et al. Hybrid particle swarm optimization for pure integer linear solid transportation problem
Dellino et al. Metamodel-based robust simulation-optimization: An overview
Schraiber A path integral formulation of the Wright–Fisher process with genic selection