A Decision Making Optimization Method for Mammography CAD using CBIR Approach

Author(s):  
Yihua Lan ◽  
Yong Zhang ◽  
Haozheng Ren ◽  
Ming Li
Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.


2012 ◽  
Vol 532-533 ◽  
pp. 566-570
Author(s):  
Lei Wang ◽  
De Chen Zhan ◽  
Lan Shun Nie ◽  
Dian Hui Chu ◽  
Xiao Fei Xu

Decentralized multi-project environment is very common in modern times, and the dynamic resource control problem for this project environment has attracted more attention. Traditional optimization method for multi-project based on the centralization in decision making does not suit for solving this problem any more. In this paper, we analyze the distributed decision making process for the dynamic resource control in the decentralized multi-project environment, and present a multi-agent system model for this problem. Using combinatorial exchange based on market, we design a negotiation mechanism to cope with the time disruptions in the stage of project execution. Computational results show that the combinatorial exchange mechanism could solve the problem effectively and has a powerful controllability for the different weights of the multiple projects.


Author(s):  
Reza Farzipoor Saen

Supplier selection is a multiple criteria decision making problem that the selection process mainly involves evaluating a number of suppliers according to a set of common criteria for selecting suppliers to meet business needs. Suppliers usually offer volume discounts to encourage the buyers to order more. To select suppliers in the presence of both volume discounts and imprecise data, this chapter proposes an optimization method. A numerical example demonstrates the application of the proposed method.


Author(s):  
Tamio Shimizu ◽  
Marley Monteiro de Carvalho ◽  
Fernando Jose Barbin

In the multiple goal function problems, there is no optimum solution fully satisfying all goals at the same time. The individual goal’s functions are, in general, conflicting and it is not possible to have an optimization method to solve the problem. There is usually a consensus solution satisfying minimal criteria of optimum values for each individual goal function. This consensus is based on the Pareto’s principle presented in chapter nine. The optimal decision making in problems with multiple goals will be analyzed at the end of this chapter (Goicoechea et al., 1982; Keeney & Raiffa, 1976; Dyson, 1990; Saaty, 1980, 1994; Bonabeau, 2003; Charan, 2001; Choo, 1998; Day et al., 1997). In considering restrictions across several scenarios, the problem solution becomes more difficult due to the high number of possible combinations of goal functions and scenarios to be considered.


Author(s):  
Vishal Mahale ◽  
Jayashree Bijwe ◽  
Sujeet Sinha

Good friction materials should satisfy diverse and contradictory performance requirements such as adequate friction ( µ ≈ 0.35–0.45), resistance to wear, fade, squeal, judder, etc. in consort with good recovery and less noise producing tendency. To achieve center point of all these conflicting criteria and selection of best overall performing friction material is multiple criteria decision making (MCDM) problem and very difficult task. Decision maker can easily make decision with single criteria without the help of any optimization tool by maximizing beneficial criteria and minimizing non-beneficial criteria. However, it is extremely challenging task if decision making involves several number of conflicting criteria. Few techniques are reported in the literature such as ‘multiple criteria decision model’, ‘Multi-attribute decision model’, ‘extension evaluation method’ (EEM), etc. for performance ranking of friction materials. However, the simplicity, reliability, applicability, time devoted for the analysis, etc. are always most important aspects of selecting a right tool for the analysis. In this paper application of a technique ‘multiple objective optimization on the basis of ratio analysis’ (MOORA) has been first time employed for performance ranking of friction materials. A comparative study of MOORA and currently used methods MCDM and EEM are also presented. MOORA proved to be the best tool based on the criteria such as simple to use, fast, flexible, and efficient one.


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