iosr-Jm   Volume-13 ~ Issue-2 ~ Mar-Apr 2017

Abstract: Goal programming is a branch of multi-objective optimization, which in turn is a branch of multi-criteria decision analysis, which is an optimization programming. Goal programming models are very similar to linear programming models whereas linear programs have one objective and goal programming can have several objectives. One of the most difficult decision problems in marketing is the determination of optimum sales allocation as a part among sales of report. This paper presents the development process of a goal programming model for the resolution of sales policy which includes all exclusive product line sold in numerous sales territory.

Keywords: Goal programming model, Sales allocation

[1]. Benayoun, R., Montgolfier J., Tergny, J., Laritchev,O., 1971.Linear programmingwith multiple objective functions :Step method (STEM) Mathematical programming 1,366-375.
[2]. Buchanan, J.T., n1997. A naïve approach for solving MCDM problems:The GUESS method. Journal of the Operational Research Society 48,202-206.
[3]. Caballero, R., Rey, L., Ruiz, F., 1996.Determination of satisfying and efficientsolutions in convex multi-objective programming.Optimization 37, 125-137.
[4]. Caballero, R., Gomez, T., Lopez del Amo, M.P., Luque, M., Martin, J., Ruiz, F., 2002a. Using interactive multiple objective methods to determine the budget assignmentto the hospitals of a sanitary system.In: Trzaskalik, T. (Ed), Multiobjective and Goal programming. Springer-Verlag, Berling, pp. 209-220.
[5]. Caballero, R., Luque, M., Molina, J., Ruiz, F., 2002b. PROMOIN:An interactivesystem for multiobjective programming.International Journal On InformationTechnologies and Decision Making 1, 635-656.

Abstract: Empirical investigation of return dynamics leads searchers to introduce CGMY model with a particular parameter useful in characterizing the fine structure of several type of stochastic process whether the data are free or include diffusion component and whether the process contains indefinite activities and finite/in finite variation. In this paper, we summarize theoretical searcher work; this provides a CGMY-FT closed form solution algorithm for pricing option. For ac- curacy and validation we implement our method to price European call options and compare the results to a numerical simulation. Math. Subject Classification: 60H15

Key Words: CGMY model, Option pricing, Levy process, Fourier transform ...

[1]. G Bakshi...............

Abstract: Approaches to an analytic description of vertex located discrete sets are presented. They are based on algebraic-topological features of the sets and properties of functions over them. One is a polyhedral-surface approach that represents a set as an intersection of its convex hull (a combinatorial polytope) and a circumscribed surface. Another one describes a set as an intersection of surfaces. These are applied for deriving various analytic representations of such sets as the Boolean set, binary set, permutation matrices set, the set of Boolean vectors with a given number of ones, and the cross-polytope vertex set..............

Keywords: Combinatorial Set, Continuous Functional Representation, Discrete Optimization, Lagrangian, The Boolean Set, The Permutation Set

[1] M.L. Balinski, A. J. Hoffman, Polyhedral Combinatorics: Dedicated to the Memory of D.R.Fulkerson (NY: Elsevier Science Ltd,
1978).
[2] V.A.Yemelichev, M.M. Kovalev, M.K. Kravtsov, Polytopes, graphs and optimisation (Cambridge: Cambridge University Press,
1984).
[3] W.R. Pulleyblank, Edmonds, matching and the birth of polyhedral combinatorics, Documenta Mathematica, Extra Volume ISMP,
2012, 181-197.
[4] Y.G. Stoyan, S.V. Yakovlev, Mathematical models and optimization methods in Geometric Design (Kiev: Naukova Dumka, 1986).
[5] C. Courcoubetis, R. Weber, Pricing Communication Networks: Economics, Technology and Modelling. (West Sussex, Hoboken:
Wiley, 2003).

Abstract: Malaria is a life threatening blood disease which is caused by parasites transmitted to humans through the bite of the Anopheles mosquito. An infected mosquito bites a human and transmits the parasites which multiply in the host's liver before infecting and destroying red blood cells. In this research work, the model equations were obtained using several known clinical and biological information with the human population subdivided into susceptible, infected, recovered and therapy classes while the vector population is divided into the susceptible and infected classes. The equilibrium states were obtained and the endemic state analysed for stability. The result shows that the non-zero equilibrium state will be stable if 𝐹(0)𝐺′ (0) > 𝑂 and unstable when otherwise.

Keywords: Stability, Characteristic Equation, Malaria, Latency.

[1]. G. H. Bledsoe, Malaria Primer for Clinicians in the United State, South. Med. J1998, 12; Pp 1197-1204.
[2]. J.D. Charlwood, T. Smith, P. F. Billingsley, W. Takken, E. Lyimo, & J. Meuwissen, Survival and Infection Probabilities of
Anthropophagic Anophelines from an Area of High Prevalence of Plasmodium Falciparum in Humans, Bull. Entomol L.Res,, 1997,
87 : Pp. 445-453.
[3]. M. B. Hoshen, R. Heinrich, W. D. Stein, & H. Ginsburg, Mathematical Modeling of the Within-host Dyamics of Plasmodium
Falciparum. Parasitology. 2001, 121: 22-235.
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R. Newmann, C. Plowe, M. H. Rodriguez, R. Sinden, L. Shusker & M. A. Tanner, Research Agenda to Underpin Malaria
Eradication. PloS Med. 8:e1000406, 2011.
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Abstract: In this work,we provide upper estimate for Fekete-Szego functional and Second Hankel determinant for the class S_fqg consisting of func- tions analytic in the unit disk U = fz 2 C : jzj < 1g and normalized by
f(0) = f0(0) = 1 = 0 and which satis_es the subordination condition.

Keywords: Coe_cient bounds,Fekete-Szego functional,Second Hankel Determinant and Subordination Keywords

[1]. E.Kedioglu, On Subclass of univalent functions with negative coe cients.Applied Mathematics and computation,146(2003)351-358
[2]. Fekete,M.Szego, Einebemerkung uber ungerade functionen.London Math.Soc.8 (1933)85-89.
[3]. 8
[4]. Marjono and D.K.Thomas, The Second Hankel Determinant of Func- tions Convex in One Direction.International Jornal of Mathematical Analysis Vol. 10,(2016)no. 9, 423-428
[5]. R.K.Raina andJ.Sokol, On Coe cient Estimate For A Class of Starlike Functions, 2000 Mathematicc Subject Classi cation. Primary 30C45

Abstract: An operator means a bounded linear operator on Hilbert span. This paper proves the assertion made in its title. Following theorem yields the famous result AB + BA* = I = A*B + BA (1) Where A and B are the bounded linear operator on a Hilbert span H. where B* is self adjoint satisfying the above equation. After modification of this equation some interesting results are obtained.

[1]. Simmons, G.F.: Introduction to topology and modern analysis. McGraw-Hill, New York (1963).
[2]. Rudin, Walter: Functional analysis (1981).
[3]. Duggal B.P. and Khalagai J.M.: On operator equation AB + BA* = A*B + BA = I, Indian J. Pure Appli. Math., 13(H), 1376-1383
November 1983.
[4]. Duggal B.P. and Khalagai J.M.: On operator equation AB + B*A = A*B + BA = I, Math Japan, 26(1981)
[5]. R. Nakamato: On the operator equation THT = K Math. Japan; 18 (1973), PP. 251-252.

Abstract: This paper presents a methodology for applying the elements of graph theory to modeling forensic investigations. This methodology uses well established principles of graph theory to model any forensic investigation and thus mathematically evaluate the elements of a case, including the probabilities associated with specific suspects

Keywords: Forensics, Graph Theory, Mathematical Modeling

[1]. Easttom, C. (2017). Utilizing Graph Theory to Model Forensic Examination. International Journal of Innovative Research in Information Security (IJIRIS), 4(2).
[2]. Balakrishnan, V.K. (2010). Introductory Discrete Mathematics. Mineola, New York: Dover Publications
[3]. Deo, N. (2016). Graph Theory with Applications to Engineering and Computer Science. Mineola, NY: Dover Publications
[4]. Wang, W., & Daniels, T. E. (2006, September). Diffusion and Graph Spectral Methods for Network Forensic Analysis. In Proceedings of the 2006 workshop on New security paradigms (pp. 99-106). ACM.
[5]. Ahlswede, R., Cai, N., Li, S. Y., & Yeung, R. W. (2000). Network information flow. IEEE Transactions on information theory, 46(4), 1204-1216

Abstract: Exact extreme value distribution is one of the most important compound distributions which is based on the theory of the maximum of random variable of random numbers. This distribution uses partial duration series (PDS) data to analyze extreme hydrological. This distribution is presented with its properties and graphical representations. Moments (MOM), maximum likelihood (ML) and Bayesian - based on non-informative and informative prior- methods are used to estimate the unknown parameters of the distribution. Markov Chain Monte Carlo (MCMC) technique is used to compute the Bayesian estimates. The simulation is performed to investigate and compare between the estimators with different sizes and a set of the parameter's values. In the sense of the mean squared error (MSE), the results showed that Bayesian -based on informative prior- method is the best estimation method.

Keywords: Exact extreme value distribution, maximum likelihood, Bayesian estimation, MCMC.

[1]. Todorovic, P., On some problems involving random number of random variables, The Annals of Mathematical Statistics, 41(3),
1970, p. 1059-1063.
[2]. Todorovic, P. and Zelenhasic, E., A stochastic model for flood analysis, Water Resources Research, 6(6) 1970, p. 1641-1648.
[3]. Kotb, N.S.A., El-Gohary, M.M. and El-Helbawy, A.T. , Analysis of Flood Frequency Distribution, Journal of Faculty of Commerce
Al-Azhar University Girls Branch, 19, 2001, p. 5-25.
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494.
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series,. Journal of hydrology, 420, 2012, p. 59-71.

Abstract: In this paper, an attempt has been made to study deterministic inventory models for deteriorating items with variable holding cost. This model has been developed considering demand function as quadratic with respect to time and salvage value is associated to the deteriorated items. At the end numerical example with sensitivity analysis also presented.

Keywords: Variable holding cost, Deterioration, Quadratic demand, Inventory

[1]. Ajanta Roy , 2008, An Inventory model for deteriorating items with price dependant demand and time-varying holding cost, AMO-Adv modeling and optim, volume 10, number 1
[2]. Amutha R, Chandrasekaran E, (2013), An Inventory Model for constant demand with shortages under permissible delay in payments, IOSR J of Math. (IOSR-JM) Vol 6 issue 5 (May –June 2013) ,PP 28-33
[3]. Chakraborti T. and Chaudhuri K.S., (1996) An EOQ model for items with linear trend in demand and shortages in all cycles Int. Jour of Production Eco,49,205-213
[4]. Giri B.C and Chaudhuri K.S.,(1997) Heuristic model for deteriorating items with shortages Int. Jour of System Science,28,153-159
[5]. Goyal S.K and Giri. B.C., (2001), Recent trends in modeling of deteriorating inventory European Jour of Ops resh, Vol.134, pp.1-16.