Haridas Kumar DasUniversity of Dhaka · Department of Mathematics
Haridas Kumar Das
B.S. M.S. (Dhaka University); M.S. (Concordia University); Graduate Teaching Associate (Oklahoma State University)
About
36
Publications
6,869
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
55
Citations
Introduction
I'm Haridas Kumar Das, a Ph.D. candidate at the Department of Mathematics at Oklahoma State University, USA. I have a BS and MS in Mathematics from Dhaka University and a second master's in mathematics from Concordia University. My research interests include Epidemiology, Data-Driven Methods, and Machine Learning, focusing on epidemic forecasting. My current project uses data to design effective strategies to control epidemics in metapopulation using epidemiological and data-driven modeling.
Additional affiliations
Education
May 2006 - December 2012
Publications
Publications (36)
Introduction
Mpox (formerly monkeypox) is an infectious disease that spreads mostly through direct contact with infected animals or people's blood, bodily fluids, or cutaneous or mucosal lesions. In light of the global outbreak that occurred in 2022–2023, in this paper, we analyzed global Mpox univariate time series data and provided a comprehensiv...
We calculate epidemic thresholds and investigate the dynamics of a disease in a networked metapopulation model. To study the specific role of mobility levels and network geometry, we utilize the SIR-Network model and consider a range of geometric structures. For \emph{star-shaped} networks where all nodes only connect to a center, we obtain the sam...
The main object of this paper is to study doubly stochastic matrices with majorization and the Birkhoff theorem. The Perron-Frobenius theorem on eigenvalues is generalized for doubly stochastic matrices. The region of all possible eigenvalues of n-by-n doubly stochastic matrix is the union of regular (n – 1) polygons into the complex plane. This st...
There is a growing need for integer solutions in industries, production units, etc. Specifically, there is an increasing demand to develop precise methods for solving integer-programming problems (IPPs). In this paper, we propose a new algorithm for solving IPPs in a general form by combining two decomposition techniques: Benders decomposition (BD)...
This paper proposes a heuristic algorithm for the computation of Nash equilibrium of a bi-matrix game, which extends the idea of a single payoff matrix of two-person zero-sum game problems. As for auxiliary but making the comparison, we also introduce here the well-known definition of Nash equilibrium and a mathematical construction via a set-value...
This paper studies some decomposition methods, including Dantzig-Wolfe decomposition (DWD), decomposition-based pricing (DBP), Benders decomposition (BD), and a recently proposed improved decomposition (ID) method for solving linear programs (LPs). The authors then develop a new decomposition algorithm for solving LPs in a general form, allowing au...
The present study deals with two person zero sum game problem and fuzzy linear programming (FLP) problem, and then development of an algorithm using FLP. To accomplish this goal, the two person zero sum game problems were first converted into linear programming (LP) problems and then by using FLP the solution of the problem was obtained. The new me...
In this paper, we study continuous frames in Hilbert spaces using a family of linearly independent vectors called coherent state (CS) and applying it in any physical space. To accomplish this goal, the
standard theory of frames in Hilbert spaces, using discrete bases, is generalized to one where the basis vectors may be labeled using discrete, cont...
In this paper, we study continuous frames in Hilbert spaces using a family of linearly independent vectors called coherent state (CS) and applying it in any physical space. To accomplish this goal, the standard theory of frames in Hilbert spaces, using discrete bases, is generalized to one where the basis vectors may be labeled using discrete, cont...
This paper is based on the analytic and computational solution procedures of Gröbner basis and its applications. We show the behavior of the ideals generated by polynomials from a polynomial ring. We also present the idea of a zero dimensional ideal and use of this ideal to solve system of polynomial equations. We then introduce an algorithmic proc...
not available Dhaka Univ. J. Sci. 65(2): 167-168, 2017 (July)
In this paper, we study on the well-known procedure of quadratic programming (QP) and its corresponding linear programming (LP) problem. We then introduce a LP problem corresponding to the QP problem. Unfortunately, an unboundedness question arises into the new converting LP problem. We then modify the converted LP problem that overcomes the unboun...
This paper improves a game theoretic algorithm and develops its computer oriented program using MATHEMATICA for solving two person zero sum game problems. The algorithm and computer algebra are drawn upon mainly from two sources, namely the papers H. K. Das, Saha and Hasan5; H. K. Das and Hasan6 being able to solve two person zero sum game problems...
Objective of this paper is to analyze on the decomposition based pricing (DBP) method for solving two person zero sum game problems. Decomposition based algorithms have been developed which is able to solve two person zero sum game problems with single payoff elements using the linear programming (LP). To develop this procedure, idea of DBP method...
This paper develops a decompose procedure for finding the optimal solution of convex and concave Quadratic Programming (QP) problems together with general Non-linear Programming (NLP) problems. The paper also develops a sophisticated computer technique corresponding to the author's algorithm using programming language MATHEMATICA. As for auxiliary...
In this paper, we improve a combined algorithm and develop a uniform computer technique for solving constrained, unconstrained Non Linear Programming (NLP) and Quadratic Programming (QP) problems into a single framework. For this, we first review the basic algorithms of convex and concave QP as well as general NLP problems. We also focus on the dev...
In this thesis we study an example of a recently proposed technique of integral quantization by looking at the Poincaré group in (1+1)-space-time dimensions, denoted P_+^{\uparrow}(1,1), which contains the affine group of the line as a subgroup. The cotangent bundle of the quotient of P_+^{\uparrow}(1,1) by the affine group has the natural structur...
In this paper, we develop a new Decomposition-Based Pricing (DBP) procedure to filter
the unnecessary decision ingredients from large scale mixed integer programming (MIP)
problem, where the variables are in huge number will be abated and the complicacy of
restrictions will be straightforward. We then develop a generalized computer technique
corres...
The role of one dimensional(1-D) algorithm in Non Linear Programming (NLP) problems, has been studied in Das and Hasan [2 ] (2013) and Choo& Kim[1] (1987). In this paper, we develop computer techniques to verify Choo and Kim’s method for solving 1-D NLP problems. We also study on the 1-D simplex search algorithm and then construct a code correspond...
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...
In this paper, we study the methodology of primal dual solutions in Linear Programming (LP) & Linear Fractional Programming (LFP) problems. A comparative study is also made on different duals of LP & LFP. We then develop an improved decomposition approach for showing the relationship of primal and dual approach of LP & LFP problems by giving algori...
In this paper, we introduce a computer-oriented technique for solving Linear Fractional Bounded Variables (LFBV) problem by converting it into a single linear programming (LP) problem. We develop this computer technique using programming language MATHEMATICA. This technique also shows all the solutions step by step. We demonstrate our technique by...
An unconstrained problem with nonlinear objective function has many applications. This is often viewed as a discipline in and of itself. In this paper, we develop a computer technique for solving nonlinear unconstrained problems in a single framework incorporating with Golden section, Gradient Search method. For this, we first combine this algorith...
Management Sciences (MS), big Group of Companies and Industries or Government Policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. In this paper, after formulating these models into LP, we developed D...
In this paper, we study the methodology of primal dual solutions in Linear Programming (LP) & Linear Fractional Programming (LFP) problems. A comparative study is also made on different duals of LP & LFP. We then develop an improved decomposition approach for showing the relationship of primal and dual approach of LP & LFP problems by giving algori...
An unconstrained problem with nonlinear objective function has many applications. This is often viewed as a discipline in and of itself. In this paper, we develop a computer technique for solving nonlinear unconstrained problems in a single framework incorporating with Golden section, Gradient Search method. For this, we first combine this algorith...
The aim of this thesis is to develop new algorithms for solving Non Linear Programming (NLP) Problems & Linear Fractional Programming (LFP) problems by using the Lagrangian relaxation & decomposition. For this, we first computationally verify Choo and Kim’s one dimensional (1-D) simplex search method for solving single variable NLP problems and dev...
In this paper, we improve an algorithm and develop its computer oriented program which is able to solve any game problem with single payoff elements within a single framework. We develop this computer technique by using the programming language MATHEMATICA. We will show the efficiency of our algorithm and its program by analyzing a number of numeri...
In this paper, we improve an algorithm and develop its computer oriented program which is able to solve any game problem with single payoff elements within a single framework. We develop this computer technique by using the programming language MATHMATICA. We will show the efficiency of our algorithm and its program by analyzing a number of numeric...
Game theory is the formal study of decision-making where several players must make choices that potentially affect the interests of the other players. In this paper, we develop a combined computer oriented technique for solving game problems. In this technique, we implement Minimax-Maximin method, rectangular game, and convert the resulting game in...
Game theory is the formal study of decision-making where several players must make choices that potentially affect the interests of the other players. In this paper, we develop a combined computer oriented technique for solving game problems. In this technique, we implement Minimax-Maximin method, rectangular game, and convert the resulting game in...
Questions
Questions (2)
Equation: $(eiaXf)=f(ax)$, where $X$ may be unbounded operator and $a in R>0$. I have found something but I am not convinced. The important point: Operator $X$ is not in terms of $a$ and the Hilbert space L^2(R>0, dx/x).
Thank you in advance.