scholarly journals Optimization of a complex hydropower development operation using HEC-ResSim

2022 ◽  
Vol 1216 (1) ◽  
pp. 012017
Author(s):  
E I Tică ◽  
K Ahmad-Rashid ◽  
O V Sima ◽  
F Popa ◽  
O Nedelcu ◽  
...  
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Energy Generation ◽  
Simplex Algorithm ◽  
Hydropower Development ◽  
Hydropower Plants ◽  
The Mean ◽  
One Year ◽  
Revised Simplex Algorithm

Abstract In this paper HEC-ResSim is applied for a complex hydropower development formed by five reservoirs and related hydropower plants. There were considered characteristics of five existing hydropower developments in Romania, for which three reservoirs are with annual regulation and two with daily regulation. The objective function was the realization of a planned energy generation for one year (the mean hydrological year). Obtained results are very close to those obtained applying linear programming, a revised simplex algorithm.

Revised simplex algorithm for linear programming on GPUs with CUDA

2018 ◽  
Vol 77 (22) ◽  
pp. 30035-30050 ◽  
Author(s):  
Lili He ◽  
Hongtao Bai ◽  
Yu Jiang ◽  
Dantong Ouyang ◽  
Shanshan Jiang
Keyword(s):  
Linear Programming ◽  
Simplex Algorithm ◽  
Revised Simplex Algorithm

A Decision Support System for Solving Linear Programming Problems

2014 ◽  
Vol 6 (2) ◽  
pp. 46-62
Author(s):  
Nikolaos Ploskas ◽  
Nikolaos Samaras ◽  
Jason Papathanasiou
Keyword(s):  
Linear Programming ◽  
Decision Support ◽  
Simplex Algorithm ◽  
Decision Makers ◽  
Web Interface ◽  
Web Based ◽  
Linear Programming Problems ◽  
Revised Simplex Algorithm ◽  
The Given ◽  
Programming Algorithms

Linear programming algorithms have been widely used in Decision Support Systems. These systems have incorporated linear programming algorithms for the solution of the given problems. Yet, the special structure of each linear problem may take advantage of different linear programming algorithms or different techniques used in these algorithms. This paper proposes a web-based DSS that assists decision makers in the solution of linear programming problems with a variety of linear programming algorithms and techniques. Two linear programming algorithms have been included in the DSS: (i) revised simplex algorithm and (ii) exterior primal simplex algorithm. Furthermore, ten scaling techniques, five basis update methods and eight pivoting rules have been incorporated in the DSS. All linear programming algorithms and methods have been implemented using MATLAB and converted to Java classes using MATLAB Builder JA, while the web interface of the DSS has been designed using Java Server Pages.

scholarly journals Linear Programming and Fuzzy Optimization to Substantiate Investment Decisions in Tangible Assets

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 121
Author(s):  
Marcel-Ioan Boloș ◽  
Ioana-Alexandra Bradea ◽  
Camelia Delcea
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Hybrid Model ◽  
Fuzzy Numbers ◽  
Investment Decision ◽  
Fuzzy Optimization ◽  
Simplex Algorithm ◽  
Fuzzy Variables ◽  
Decision Variables ◽  
Tangible Assets

This paper studies the problem of tangible assets acquisition within the company by proposing a new hybrid model that uses linear programming and fuzzy numbers. Regarding linear programming, two methods were implemented in the model, namely: the graphical method and the primal simplex algorithm. This hybrid model is proposed for solving investment decision problems, based on decision variables, objective function coefficients, and a matrix of constraints, all of them presented in the form of triangular fuzzy numbers. Solving the primal simplex algorithm using fuzzy numbers and coefficients, allowed the results of the linear programming problem to also be in the form of fuzzy variables. The fuzzy variables compared to the crisp variables allow the determination of optimal intervals for which the objective function has values depending on the fuzzy variables. The major advantage of this model is that the results are presented as value ranges that intervene in the decision-making process. Thus, the company’s decision makers can select any of the result values as they satisfy two basic requirements namely: minimizing/maximizing the objective function and satisfying the basic requirements regarding the constraints resulting from the company’s activity. The paper is accompanied by a practical example.

scholarly journals Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems

2020 ◽  
pp. 1-14
Author(s):  
Sanjay Jain ◽  
Adarsh Mangal
Keyword(s):  
Linear Programming ◽  
Numerical Solution ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Simplex Algorithm ◽  
Multi Objective ◽  
Linear Objective Function ◽  
Gauss Elimination ◽  
Linear Programming Problems

In this research paper, an effort has been made to solve each linear objective function involved in the Multi-objective Linear Programming Problem (MOLPP) under consideration by AHA simplex algorithm and then the MOLPP is converted into a single LPP by using various techniques and then the solution of LPP thus formed is recovered by Gauss elimination technique. MOLPP is concerned with the linear programming problems of maximizing or minimizing, the linear objective function having more than one objective along with subject to a set of constraints having linear inequalities in nature. Modeling of Gauss elimination technique of inequalities is derived for numerical solution of linear programming problem by using concept of bounds. The method is quite useful because the calculations involved are simple as compared to other existing methods and takes least time. The same has been illustrated by a numerical example for each technique discussed here.

scholarly journals Generalised Single-Valued Neutrosophic Number and Its Application to Neutrosophic Linear Programming

2020 ◽  
pp. 180-214
Author(s):  
Nirmal Kumar Mahapatra ◽  
Tuhin Bera
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Simplex Method ◽  
Real Life ◽  
Simplex Algorithm ◽  
Real Life Problem ◽  
Crisp Linear Programming ◽  
Neutrosophic Number

In this chapter, the concept of single valued neutrosophic number (SVN-Number) is presented in a generalized way. Using this notion, a crisp linear programming problem (LP-problem) is extended to a neutrosophic linear programming problem (NLP-problem). The coefficients of the objective function of a crisp LP-problem are considered as generalized single valued neutrosophic number (GSVN-Number). This modified form of LP-problem is here called an NLP-problem. An algorithm is developed to solve NLP-problem by simplex method. Finally, this simplex algorithm is applied to a real-life problem. The problem is illustrated and solved numerically.

scholarly journals Comments on Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems by Sanjay Jain and Adarsh Mangal

2020 ◽  
Vol 06 (09) ◽  
pp. 94-96
Author(s):  
Chandra Sen
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Simplex Method ◽  
Simplex Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Excellent Research ◽  
Gauss Elimination ◽  
Linear Programming Problems ◽  
Averaging Techniques

An excellent research contribution was made by Sanjay and Adarsh in using Gauss Elimination Technique and AHA simplex method for solving multi-objective optimization (MOO) problems. The method was applied for solving MOO problems using Chandra Sen's technique and several other averaging techniques. The formulation of multi-objective function in the averaging techniques was not perfect. The example was also not appropriate.

scholarly journals A Proposed Technique for Solving Linear Fractional Bounded Variable Problems

2012 ◽  
Vol 60 (2) ◽  
pp. 223-230
Author(s):  
H.K. Das ◽  
M. Babul Hasan
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Programming Language ◽  
Simplex Algorithm ◽  
Computational Effort ◽  
New Method ◽  
Bounded Variables ◽  
Primal Dual ◽  
Dual Simplex ◽  
Dual Simplex Algorithm

In this paper, a new method is proposed for solving the problem in which the objective function is a linear fractional Bounded Variable (LFBV) function, where the constraints functions are in the form of linear inequalities and the variables are bounded. The proposed method mainly based upon the primal dual simplex algorithm. The Linear Programming Bounded Variables (LPBV) algorithm is extended to solve Linear Fractional Bounded Variables (LFBV).The advantages of LFBV algorithm are simplicity of implementation and less computational effort. We also compare our result with programming language MATHEMATICA.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11522 Dhaka Univ. J. Sci. 60(2): 223-230, 2012 (July) 

Developing Schedule With Linear Programming (Case Study: STTF II Project Komplek Sukamukti Banjaran)

2020 ◽  
Vol 4 (02) ◽  
pp. 34-45
Author(s):  
Naufal Dzikri Afifi ◽  
Ika Arum Puspita ◽  
Mohammad Deni Akbar
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Time Limit ◽  
Minimum Time ◽  
Service Cost ◽  
Trade Off ◽  
Overtime Work ◽  
The Cost

Shift to The Front II Komplek Sukamukti Banjaran Project is one of the projects implemented by one of the companies engaged in telecommunications. In its implementation, each project including Shift to The Front II Komplek Sukamukti Banjaran has a time limit specified in the contract. Project scheduling is an important role in predicting both the cost and time in a project. Every project should be able to complete the project before or just in the time specified in the contract. Delay in a project can be anticipated by accelerating the duration of completion by using the crashing method with the application of linear programming. Linear programming will help iteration in the calculation of crashing because if linear programming not used, iteration will be repeated. The objective function in this scheduling is to minimize the cost. This study aims to find a trade-off between the costs and the minimum time expected to complete this project. The acceleration of the duration of this study was carried out using the addition of 4 hours of overtime work, 3 hours of overtime work, 2 hours of overtime work, and 1 hour of overtime work. The normal time for this project is 35 days with a service fee of Rp. 52,335,690. From the results of the crashing analysis, the alternative chosen is to add 1 hour of overtime to 34 days with a total service cost of Rp. 52,375,492. This acceleration will affect the entire project because there are 33 different locations worked on Shift to The Front II and if all these locations can be accelerated then the duration of completion of the entire project will be effective

scholarly journals Incomplete Kawasaki disease - a diagnostic and therapeutic challenge

2014 ◽  
Vol 9 (4) ◽  
pp. 30-35
Author(s):  
S Datta ◽  
S Maiti ◽  
G Das ◽  
A Chatterjee ◽  
P Ghosh
Keyword(s):  
Kawasaki Disease ◽  
Intravenous Immunoglobulin ◽  
Incomplete Kawasaki Disease ◽  
Duration Of Symptoms ◽  
Clinical Criteria ◽  
Echocardiographic Finding ◽  
2D Echocardiography ◽  
Acquired Heart Disease ◽  
The Mean ◽  
One Year

Background The diagnosis of classical Kawasaki Disease was based on clinical criteria. The conventional criteria is particularly useful in preventing over diagnosis, but at the same time it may result in failure to recognize the incomplete form of Kawasaki Disease. Objective To suspect incomplete Kawasaki Disease, because early diagnosis and proper treatment may reduce substantial risk of developing coronary artery abnormality which is one of the leading causes of acquired heart disease in children. Method Nine cases of incomplete Kawasaki Disease were diagnosed over a period of one year. The diagnosis of incomplete Kawasaki Disease was based on fever for five days with less than four classical clinical features and cardiac abnormality detected by 2D- echocardiography. A repeat echocardiography was done after 6 weeks of onset of illness. The patients were treated with Intravenous Immunoglobulin and/or aspirin. Result The mean age of the patients was 3.83 years and the mean duration of symptoms before diagnosis was 12.1 days. Apart from other criteria all of our patients had edema and extreme irritability. All the patients had abnormal echocardiographic finding. Five patients received only aspirin due to nonaffordability of Intravenous Immunoglobulin and four patients received both aspirin and Intravenous Immunoglobulin, but the outcome was excellent in all the cases. Conclusion Incomplete Kawasaki Disease can be diagnosed with more awareness and aspirin alone may be used as a second line therapy in case of non affordability of Intravenous Immunoglobulin. Journal of College of Medical Sciences-Nepal, 2013, Vol-9, No-4, 30-35 DOI: http://dx.doi.org/10.3126/jcmsn.v9i4.10234

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