A multi-objective genetic stock portfolio mining approach with investor's requests

2014 ◽  
Author(s):  
Chun-Hao Chen ◽  
Ching-Yu Hsieh
Keyword(s):  
Genetic Stock ◽  
Multi Objective ◽  
Stock Portfolio

scholarly journals Optimizing Stock Portfolio with Markowitz Method as a Reference for Investment Community Decisions

2021 ◽  
Vol 2 (2) ◽  
pp. 71-76
Author(s):  
Viona Prisyella Balqis ◽  
Subiyanto Subiyanto ◽  
Sudradjat Supian
Keyword(s):  
Portfolio Optimization ◽  
Multi Objective Optimization ◽  
Expected Return ◽  
Multi Objective ◽  
Portfolio Returns ◽  
Maximum Profit ◽  
The Right ◽  
Stock Portfolio

An investor who wants to invest by avoiding risk makes investors tend to choose investments with the same expected return and the smallest or lowest possible risk. Therefore, investors expect to be able to maximize profits and minimize risk at the same time in investing. In a stock portfolio, it can be done by investing the funds owned by investors into several stocks so that it can reduce the risk of losses that will occur simultaneously. In choosing the right company to invest in with consideration of expected return and risk, a multi-objective optimization with multivariate objects can be used so that it can meet the expectations of investors. The portfolio concept introduced by Markowitz is a portfolio optimization intended for standard investors because it only refers to one explanation of portfolio returns. The Markowitz method can produce an optimal stock portfolio by considering the expected return and risk simultaneously so that the maximum profit can be obtained without eliminating the existing risk.

An Ultrastructural Comparison of Hepatocytes from ADH+ and ADH−Peromyscus Maniculatus

1996 ◽  
Vol 54 ◽  
pp. 30-31
Author(s):  
J. T. Ellzey ◽  
D. Borunda ◽  
B. P. Stewart
Keyword(s):  
South Carolina ◽  
Adult Male ◽  
Uranyl Acetate ◽  
Model System ◽  
Deer Mice ◽  
En Bloc ◽  
Genetic Stock ◽  
Hepes Buffer ◽  
Transmission Electron ◽  
Color Scanner

Genetically alcohol deficient deer mice (ADHN/ADHN) (obtained from the Peromyscus Genetic Stock Center, Univ. of South Carolina) lack hepatic cytosolic alcohol dehydrogenase. In order to determine if these deer mice would provide a model system for an ultrastructural study of the effects of ethanol on hepatocyte organelles, 75 micrographs of ADH+ adult male deer mice (n=5) were compared with 75 micrographs of ADH− adult male deer mice (n=5). A morphometric analysis of mitochondrial and peroxisomal parameters was undertaken.The livers were perfused with 0.1M HEPES buffer followed by 0.25% glutaraldehyde and 2% sucrose in 0.1M HEPES buffer (4C), removed, weighed and fixed by immersion in 2.5% glutaraldehyde in 0.1M HEPES buffer, pH 7.4, followed by a 3,3’ diaminobenzidine (DAB) incubation, postfixation with 2% OsO4, en bloc staining with 1% uranyl acetate in 0.025M maleate-NaOH buffer, dehydrated, embedded in Poly/Bed 812-BDMA epon resin, sectioned and poststained with uranyl acetate and lead citrate. Photographs were taken on a Zeiss EM-10 transmission electron microscope, scanned with a Howtek personal color scanner, analyzed with OPTIMAS 4.02 software on a Gateway2000 4DX2-66V personal computer and stored in Excel 4.0.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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