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Robust Optimization with practical application
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The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend build a robust linear model on it, and then comparing between robust optimal results with usual optimal results.

      In this paper has been reached to the most important results, it is possible that a simple neglecting of uncertainty in the parameters' values causes a decrease in profits, so in case increase the percentage of impurities in raw materials to the maximum of their expected cases, caused a decrease in the concentration of active substance needed to produce planned amount, that make decreases production and therefore reducing of revenue the value of (67,883,826.8281) IQD per year from the expected profit, as that total of expected profit is (537,921,100) IQD, and when this value decreases because the values change randomly, the profits are (470,037,273.172) IQD in the worst expected cases. While when the robust model was applied, the total profit was (476,269,200) IQD. In contrast ensures that this value is not decreased at any random change to the value was happening, because the robust model was built in its worst-case expected. Also, it is possible to guarantee that any violation of the constraint was avoided in the event of random variations that obtain in uncertainty parameter value when applying a robust style.

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Publication Date
Sat Jul 01 2023
Journal Name
Industrial Laboratory. Materials Diagnostics
OPTIMIZATION OF PLASMA-ASSISTED DESORPTION/IONIZATIONMASS SPECTROMETRY FOR ANALYSIS OF IBUPROFEN
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In medical practice, nonsteroidal anti-inflammatory drugs (NSAIDs) are often used to treat osteoarthritis and rheumatoid arthritis. Ibuprofen is a well-known NSAID, analgesic, and antipyretic medication. This chemical is an active ingredient of several oral medications that are offered in tablet, gel pellet, and syrup forms and has higher efficacy, tolerance, and side effect rates than other compounds, including pyrazolone derivatives. We present a unique plasma-assisted desorption/ionization mass spectrometry (PADI-MS) approach for improving pharmaceutically important solids using an ibuprofen tablet as a model solid sample. The goal of the study is to create an innovative mass spectrometric method that could be used for quick and accur

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Publication Date
Sat Jun 29 2013
Journal Name
Wireless Personal Communications
A Low Cost Route Optimization Scheme for Cluster-Based Proxy MIPv6 Protocol
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Publication Date
Wed Sep 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancement of Uniformity of Solid Particles in Spouted Bed Using Stochastic Optimization
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Performance of gas-solid spouted bed benefit from solids uniformity structure (UI).Therefore, the focus of this work is to maximize UI across the bed based on process variables. Hence, UI is to be considered as the objective of the optimization process .Three selected process variables are affecting the objective function. These decision variables are: gas velocity, particle density and particle diameter. Steady-state solids concentration measurements were carried out in a narrow 3-inch cylindrical spouted bed made of Plexiglas that used 60° conical shape base. Radial concentration of particles (glass and steel beads) at various bed heights and different flow patterns were measured using sophisticated optical probes. Stochastic Genetic

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Publication Date
Sat Dec 01 2018
Journal Name
2018 Third Scientific Conference Of Electrical Engineering (scee)
An Intelligent Cognitive System Design for Mobile Robot based on Optimization Algorithm
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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Response Surface Methodology for Development and Optimization of Theophylline Pulmonary Delivery System
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The aim of the present study was to develop theophylline (TP) inhalable sustained delivery system by preparing solid lipid microparticles using glyceryl behenate (GB) and poloxamer 188 (PX) as a lipid carrier and a surfactant respectively. The method involves loading TP nanoparticles into the lipid using high shear homogenization – ultrasonication technique followed by lyophilization. The compositional variations and interactions were evaluated using response surface methodology, a Box – Behnken design of experiment (DOE). The DOE constructed using TP (X1), GB (X2) and PX (X3) levels as independent factors. Responses measured were the entrapment efficiency (% EE) (Y1), mass median

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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Wed Apr 02 2025
Journal Name
University Of Thi-qar Journal
Production of Thermostable Bioflocculant from Bacillus subtilis and Optimization of Flocculation Conditions
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Bacteria strain H7, which produces flocculating substances, was isolated from the soil of corn field at the College of Agriculture in Abu-Ghrib/Iraq, and identified as Bacillus subtilis by its biochemical /physiological characteristics. The biochemical analysis of the partially purified bioflocculant revealed that it was a proteoglycan composed of 93.2 % carbohydrate and 6.1 % protein. The effects of bioflocculant dosage, temperature, pH, and different salts on the flocculation activity were evaluated. The maximum flocculation activity was observed at an optimum bioflocculant dosage of 0.2 mL /10 mL (49.6%). The bioflocculant had strong thermal stability within the range of 30-80 °C, and the flocculating activity was over 50 %. The biofloc

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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Process Optimization Study of Pb(II) Removal by Bulk Liquid Membrane (BLM)
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   Box-Wilson experimental design method was employed to optimized lead ions removal efficiency by bulk liquid membrane (BLM) method. The optimization procedure was primarily based on four impartial relevant parameters: pH of feed phase (4-6), pH of stripping phase (9-11), carrier concentration TBP (5-10) %, and initial metal concentration (60-120 ppm). maximum recovery efficiency of lead ions is 83.852% was virtually done following thirty one-of-a-kind experimental runs, as exact through 24-Central Composite Design (CCD). The best values for the aforementioned four parameters, corresponding to the most restoration efficiency were: 5, 10, 7.5% (v/v), and 90 mg/l, respectively. The obtained experimental data had been utilized to st

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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