A Study on Multi-Objective Optimization of Abrasive Blasting Systems

2010 ◽  
Vol 126-128 ◽  
pp. 29-34 ◽  
Author(s):  
Vu Ngoc Pi ◽  
Tran Minh Duc
Keyword(s):  
Boron Carbide ◽  
Optimization Problem ◽  
Nozzle Diameter ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Nozzle Wear ◽  
The Cost ◽  
Cost Components ◽  
Abrasive Blasting

This paper introduces a study on a multi-objective optimization problem of abrasive blasting systems. The aim of the study is to find the optimum exchanged diameter of boron carbide nozzles. In the study, the effects of several parameters such as the maximum nozzle diameter, the nozzle wear and the cost components on the optimum initial nozzle diameter were taken into account. From the study, a regression model for determination of the optimum initial diameter of boron carbide nozzles was introduced.

Profit Optimization of Abrasive Blasting Systems

2008 ◽  
Vol 389-390 ◽  
pp. 392-397 ◽  
Author(s):  
Vu Ngoc Pi
Keyword(s):  
Optimization Problem ◽  
Nozzle Diameter ◽  
Profit Rate ◽  
Nozzle Wear ◽  
Profit Optimization ◽  
Maximal Profit ◽  
The Cost ◽  
Cost Components ◽  
Abrasive Blasting

This paper presents a new study on profit optimization of abrasive blasting systems. In the study, the effects of many parameters such as the air pressure, the initial nozzle diameter, the cost components and the nozzle wear on the profit rate were investigated. Based on the results of the optimization problem, regression models for determination of the optimal exchanged nozzle diameter in order to get the maximal profit rate were proposed. With “optimal diameter”, both the profit rate and the cleaning time can be reduced significantly.

Cost Optimization of Abrasive Blasting Systems: A New and Effective Way for Using Blasting Nozzles

2007 ◽  
Vol 329 ◽  
pp. 323-328 ◽  
Author(s):  
Vu Ngoc Pi ◽  
A.M. Hoogstrate
Keyword(s):  
Cost Optimization ◽  
Nozzle Diameter ◽  
New Model ◽  
Nozzle Wear ◽  
Efficiency Cost ◽  
Cleaning Cost ◽  
Cost Components ◽  
Optimal Diameter ◽  
Comprehensive Study ◽  
Abrasive Blasting

This paper introduces a new and comprehensive study on cost optimization of abrasive blasting systems. In the study, the effects of many parameters such as nozzle diameter, air pressure, efficiency, cost components as well as the effect of the nozzle wear on the cleaning cost were investigated. A new model for calculation of the optimal exchanged nozzle diameter (called “optimal diameter”) was proposed. With “optimal diameter” a new and effective way of using and making blasting nozzles was proposed and both the cleaning cost and the cleaning time can be reduced significantly.

scholarly journals Solving the Asymmetry Multi-Objective Optimization Problem in PPPs under LPVR Mechanism by Bi-Level Programing

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1667
Author(s):  
Feiran Liu ◽  
Jun Liu ◽  
Xuedong Yan
Keyword(s):  
Optimization Problem ◽  
Optimal Strategies ◽  
Decision Makers ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Present Value ◽  
Public And Private ◽  
The Public ◽  
Multi Objective ◽  
The Cost

Optimizing the cost and benefit allocation among multiple players in a public-private partnership (PPP) project is recognized to be a multi-objective optimization problem (MOP). When the least present value of revenue (LPVR) mechanism is adopted in the competitive procurement of PPPs, the MOP presents asymmetry in objective levels, control variables and action orders. This paper characterizes this asymmetrical MOP in Stackelberg theory and builds a bi-level programing model to solve it in order to support the decision-making activities of both the public and private sectors in negotiation. An intuitive algorithm based on the non-dominated sorting genetic algorithm III (NSGA III) framework is designed to generate Pareto solutions that allow decision-makers to choose optimal strategies from their own criteria. The effectiveness of the model and algorithm is validated via a real case of a highway PPP project. The results reveal that the PPP project will be financially infeasible without the transfer of certain amounts of exterior benefits into supplementary income for the private sector. Besides, the strategy of transferring minimum exterior benefits is more beneficial to the public sector than to users.

scholarly journals Multi-objective optimization of retaining wall using genetic algorithm

2021 ◽  
Vol 8 (1-2) ◽  
pp. 58-65
Author(s):  
Filip Dodigović ◽  
Krešo Ivandić ◽  
Jasmin Jug ◽  
Krešimir Agnezović
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Retaining Wall ◽  
Silty Sand ◽  
Embedment Depth ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Definition Of ◽  
The Cost

The paper investigates the possibility of applying the genetic algorithm NSGA-II to optimize a reinforced concrete retaining wall embedded in saturated silty sand. Multi-objective constrained optimization was performed to minimize the cost, while maximizing the overdesign factors (ODF) against sliding, overturning, and soil bearing resistance. For a given change in ground elevation of 5.0 m, the width of the foundation and the embedment depth were optimized. Comparing the algorithm's performance in the cases of two-objective and three objective optimizations showed that the number of objectives significantly affects its convergence rate. It was also found that the verification of the wall against the sliding yields a lower ODF value than verifications against overturning and soil bearing capacity. Because of that, it is possible to exclude them from the definition of optimization problem. The application of the NSGA-II algorithm has been demonstrated to be an effective tool for determining the set of optimal retaining wall designs.

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Marcelo Ramos Martins ◽  
Diego F. Sarzosa Burgos
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Ship Design ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Multi Objective ◽  
The Cost

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies.

Profit Optimization of Steel Shot Blasting Processes

2013 ◽  
Vol 312 ◽  
pp. 976-981
Author(s):  
Vu Ngoc Pi ◽  
Pham Hong Thai ◽  
Tran Quoc Hung
Keyword(s):  
Optimization Problem ◽  
Nozzle Diameter ◽  
Profit Rate ◽  
Shot Blasting ◽  
Maximum Profit ◽  
Steel Shot ◽  
Nozzle Wear ◽  
Profit Optimization ◽  
Cost Components ◽  
Pressure Nozzle

This paper presents a study on profit optimization of steel shot blasting systems. In the study, the influences of blasting process parameters including air pressure, nozzle diameter, cost components as well as the effect of the nozzle wear on the profit of a cleaning process were investigated. Based on the results of the optimization problem, a regression model for calculation of the optimum exchanged nozzle diameter in order to get the maximum profit rate was proposed. By using the model, both the profit and the blasting time can be reduced considerably.

scholarly journals Optimizing Replaced Nozzle Diameter of Abrasive Blasting Systems Using Experiment Technique Design

2020 ◽  
Vol 10 (11) ◽  
pp. 3920 ◽  
Author(s):  
Ngoc-Pi Vu ◽  
Xuan-Hung Le ◽  
Dinh-Ngoc Nguyen ◽  
Anh-Tung Luu ◽  
Thanh-Tu Nguyen ◽  
...  
Keyword(s):  
Regression Model ◽  
Boron Carbide ◽  
Design Of Experiment ◽  
Nozzle Diameter ◽  
Cost System ◽  
Experiment Technique ◽  
The Cost ◽  
Cleaning Cost ◽  
Abrasive Blasting

The blasting technique has been broadly utilized to prepare new surfaces for painting, engraving, etc., in industry. In fact, the minimization of the cleaning cost system is essential. However, the knowledge of this technique in terms of optimization has been poor so far. The aim of this study is to find the optimum replaced boron carbide nozzle diameter for the abrasive blasting system. The basis of the study is to find the replaced nozzle diameter to minimize the cost of the blasting system. Seven main parameters are adopted for examining their influences on the response and the optimum replaced nozzle diameter. The design of experiment (DOE) technique is utilized by using Minitab@19. The results reveal that the initial nozzle diameter has the strongest impact on the optimum replaced nozzle diameter. Furthermore, the proposed regression model has been found to be entirely insistent to the experiments. The utilization of this model can provide an effective way to simplify the calculation of the optimum initial nozzle diameter for boron carbide.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

scholarly journals Modelling and Multi-Objective Optimization of the Sulphur Dioxide Oxidation Process

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1072
Author(s):  
Mohammad Reza Zaker ◽  
Clémence Fauteux-Lefebvre ◽  
Jules Thibault
Keyword(s):  
Sulphuric Acid ◽  
Sulphur Dioxide ◽  
Variable Number ◽  
Inlet Temperature ◽  
Multi Objective Optimization ◽  
Absorption Column ◽  
Maximum Reaction Rate ◽  
Multi Objective ◽  
Maximum Reaction

Sulphuric acid (H2SO4) is one of the most produced chemicals in the world. The critical step of the sulphuric acid production is the oxidation of sulphur dioxide (SO2) to sulphur trioxide (SO3) which takes place in a multi catalytic bed reactor. In this study, a representative kinetic rate equation was rigorously selected to develop a mathematical model to perform the multi-objective optimization (MOO) of the reactor. The objectives of the MOO were the SO2 conversion, SO3 productivity, and catalyst weight, whereas the decisions variables were the inlet temperature and the length of each catalytic bed. MOO studies were performed for various design scenarios involving a variable number of catalytic beds and different reactor configurations. The MOO process was mainly comprised of two steps: (1) the determination of Pareto domain via the determination a large number of non-dominated solutions, and (2) the ranking of the Pareto-optimal solutions based on preferences of a decision maker. Results show that a reactor comprised of four catalytic beds with an intermediate absorption column provides higher SO2 conversion, marginally superior to four catalytic beds without an intermediate SO3 absorption column. Both scenarios are close to the ideal optimum, where the reactor temperature would be adjusted to always be at the maximum reaction rate. Results clearly highlight the compromise existing between conversion, productivity and catalyst weight.

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