scholarly journals SENSITIVITY ANALYSIS FOR OPTIMIZATION MODEL FOR COASTAL GROUNDWATER

2010 ◽  
pp. 167-172
Author(s):  
SUNG-HUN HONG ◽  
NAMSIK PARK
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Model ◽  
Coastal Groundwater

The job rotation scheduling problem considering human cognitive effects: an integrated approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ashkan Ayough ◽  
Farbod Farhadi ◽  
Mostafa Zandieh
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Model ◽  
Design Methodology ◽  
Heuristic Algorithms ◽  
Job Rotation ◽  
Content Type ◽  
Input Parameters ◽  
Job Rotation Scheduling ◽  
The Impact ◽  
First Time

Purpose This paper aims to unfold the role that job rotation plays in a lean cell. Unlike many studies, the authors consider heterogeneous operators with dynamic performance factor that is impacted by the assignment and scheduling decisions. The purpose is to derive an understanding of the underlying effects of job rotations on performance metrics in a lean cell. The authors use an optimization framework and an experimental design methodology for sensitivity analysis of the input parameters. Design/methodology/approach The approach is an integration of three stages. The authors propose a set-based optimization model that considers human behavior parameters. They also solve the problem with two meta-heuristic algorithms and an efficient local search algorithm. Further, the authors run a post-optimality analysis by conducting a design of experiments using the response surface methodology (RSM). Findings The results of the optimization model reveal that the job rotation schedules and the human cognitive metrics influence the performance of the lean cell. The results of the sensitivity analysis further show that the objective function and the job rotation frequencies are highly sensitive to the other input parameters. Based on the findings from the RSM, the authors derive general rules for the job rotations in a lean cell given the ranges in other input variables. Originality/value The authors integrate the job rotation scheduling model with human behavioral and cognitive parameters and formulate the problem in a lean cell for the first time in the literature. In addition, they use the RSM for the first time in this context and offer a post-optimality analysis that reveals important information about the impact of the job rotations on the performance of operators and the entire working cell.

Performance optimization model n 802.11n networks using multi-objective programming

2017 ◽  
pp. 2907-2918
Author(s):  
Carlos Arturo Castillo Medina ◽  
Octavio Jose Salcedo Parra ◽  
Miguel J. Espitia R.
Keyword(s):  
Sensitivity Analysis ◽  
Wireless Networks ◽  
Performance Optimization ◽  
Optimization Model ◽  
Performance Data ◽  
Past Performance ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Objective Programming

This project aims to develop a method to find an alternative to analyze the performance of wireless networks (for this case 802.11n) using the Multiobjetive Programming. They perform three functions with their respective objectives and constraints finds its solution. The model was validated against and past performance data against data taken from two wireless networks possess a different complement infrastructure, this in order to perform a sensitivity analysis.

Analytical Robust Design of a Gear Milling Machine Headstock

2010 ◽  
Vol 37-38 ◽  
pp. 162-165 ◽  
Author(s):  
Yong Liang Chen ◽  
Shuang Liu ◽  
Han Tao Wang ◽  
Pei Hua Gu
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Robust Design ◽  
Optimization Model ◽  
Functional Performance ◽  
Geometric Design ◽  
Design Parameters ◽  
Milling Machine ◽  
Robust Analysis ◽  
Rayleigh Method

Headstock is a key component of gear milling machine. The dynamic functional performance of the headstock is usually influenced by uncertainties of both geometric and non-geometric design parameters. A new mathematical model to represent relationships among first frequency and design parameters of the headstock were derived with Rayleigh method. Then, a larger-the-better and smaller-the-better robust analysis and optimization model was developed. The sensitivity analysis results show that height of the headstock makes a great impact on the first frequency. Through robust optimizations, the first frequency is scaled up by 3.35 percent while minimizing the variance of the first frequency.

The Buckling Optimization on Composite Beam with Hat Stiffener

2014 ◽  
Vol 953-954 ◽  
pp. 1649-1652 ◽  
Author(s):  
Jia Bo Qiu ◽  
Xi Zhu
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Optimization Model ◽  
Composite Beam ◽  
Mathematical Optimization ◽  
Latin Hypercube Design ◽  
Critical Buckling Load ◽  
Buckling Optimization ◽  
Optimal Latin Hypercube Design ◽  
Mathematical Optimization Model

The paper carried out the buckling optimization on composite beam with hat stiffener by taking ply angle as optimal variables and the critical buckling load (CBL) as the optimal objective. Firstly, the paper established the mathematical optimization model, and then carried out sensitivity analysis of ply angle through Optimal Latin Hypercube Design, finally optimized the design of the layer using Genetic Algorithm. The results show that the CBL of stiffened beam with the optimized ply angle is increased by 64% than that with initial ply angle; CBL can be increased by changing the ply angle, the sheet should adopt the 0° or 90° layer, while the surface and center of stiffener should adopt ±45° layer and the rest should be 0° or 90°.

scholarly journals Analytical Optimization for the Warehouse Sizing Problem Under Class-Based Storage Policy

2016 ◽  
Vol 12 (24) ◽  
pp. 221-248
Author(s):  
Luis F. Cardona ◽  
Leonardo Rivera ◽  
Héctor Jairo Martínez
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Model ◽  
Analytical Methods ◽  
Mathematical Proof ◽  
Linear Optimization ◽  
Optimal Configuration ◽  
Paper Study ◽  
Linear Optimization Model ◽  
Product Classification ◽  
The Impact

The aim of this paper study the impact of class-based storagepolicy basedon the optimal configuration of U-flow single command warehouses using aon an ABC product classification. For that purpose, the authors proposea non linear optimization model to minimize the expected travel distanceof the warehouse and use analytical methods to solve it.The most important contribution is to provide a mathematical proof thatregardless of the storage policy (It does not matter the specifics of theturnover pattern of the products), the optimal warehouse has a width thatis the double of its length, and the pick and deposit point should be locatedin the middle of the width of the warehouse.In addition, authors perform a sensitivity analysis that indicates that theoptimal solution is robust, meaning that a certain deviation from the op-timum layout does not impose a significant penalty on the expected traveldistance of the warehouse.

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