• Previous Article
    Electricity supply chain coordination with carbon abatement technology investment under the benchmarking mechanism
  • JIMO Home
  • This Issue
  • Next Article
    Pricing and lot-sizing decisions for perishable products when demand changes by freshness
doi: 10.3934/jimo.2020083

Application of survival theory in taxation

1. 

Ulaanbaatar State University, Ulaanbaatar, Mongolia

2. 

National University of Mongolia, Ulaanbaatar, Mongolia

* Corresponding author: Enkhbat Rentsen

Received  September 2019 Revised  January 2020 Published  April 2020

Fund Project: The second author is supported by NUM grant P2019-3751

The paper deals with the application of the survival theory in economic systems. Theory and methodology of survival is used to evaluate fiscal policy. The survival of the system reduces to a problem of maximizing a radius of a cube inscribed into a polyhedral set so-called the target-oriented purpose [1-5]. We show that the survival theory can be applied to the government fiscal policy optimizing a taxation system. Numerical simulations were conducted using Mongolian statistical data for 2015.

Citation: Badam Ulemj, Enkhbat Rentsen, Batchimeg Tsendpurev. Application of survival theory in taxation. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2020083
References:
[1]

L. T. Aščepkov, On the construction of the maximum cube inscribed in a given domain, Zh. Vychisl. Mat. i Mat. Fiz., 20 (1980), 510-513.   Google Scholar

[2]

L. T. Aščepkov and U. Badam, Models and methods of survival theory for controlled system, Vladivostok DalNauka, (2006). Google Scholar

[3]

U. Badam, A simple model of improving survival in economical systems, in Optimization and Optimal Control, Ser. Comput. Oper. Res., 1, World Sci. Publ., River Edge, NJ, 2003,287–295.  Google Scholar

[4]

U. Badam, Necessary optimality conditions in survival problems, Izv. Vyssh. Uchebn. Zaved. Mat., 2002 (2002), 18-22.   Google Scholar

[5]

U. Badam, Models and problems of survival theory for linear discrete system, Intellect Control, (2002), 35–50. Google Scholar

[6]

R. Enkhbat, Global optimization approach to Malfatti's problem, J. Global Optim., 65 (2016), 33-39.  doi: 10.1007/s10898-015-0372-6.  Google Scholar

[7]

R. EnkhbatM. V. Barkova and A. S. Strekalovsky, Solving Malfatti's high dimensional problem by global optimization, Numer. Algebra Control Optim., 6 (2016), 153-160.  doi: 10.3934/naco.2016005.  Google Scholar

[8] L. Ljungvist and T. J. Sargent, Recursive Macroeconomic Theory, The MIT Press, 2000.   Google Scholar
[9]

C. Malfatti, Memoria Sopra una Problema Stereotomico, Memoria di Matematica e di Fisica della Societa italiana della Scienze, 10 (1803), 235-244.   Google Scholar

show all references

References:
[1]

L. T. Aščepkov, On the construction of the maximum cube inscribed in a given domain, Zh. Vychisl. Mat. i Mat. Fiz., 20 (1980), 510-513.   Google Scholar

[2]

L. T. Aščepkov and U. Badam, Models and methods of survival theory for controlled system, Vladivostok DalNauka, (2006). Google Scholar

[3]

U. Badam, A simple model of improving survival in economical systems, in Optimization and Optimal Control, Ser. Comput. Oper. Res., 1, World Sci. Publ., River Edge, NJ, 2003,287–295.  Google Scholar

[4]

U. Badam, Necessary optimality conditions in survival problems, Izv. Vyssh. Uchebn. Zaved. Mat., 2002 (2002), 18-22.   Google Scholar

[5]

U. Badam, Models and problems of survival theory for linear discrete system, Intellect Control, (2002), 35–50. Google Scholar

[6]

R. Enkhbat, Global optimization approach to Malfatti's problem, J. Global Optim., 65 (2016), 33-39.  doi: 10.1007/s10898-015-0372-6.  Google Scholar

[7]

R. EnkhbatM. V. Barkova and A. S. Strekalovsky, Solving Malfatti's high dimensional problem by global optimization, Numer. Algebra Control Optim., 6 (2016), 153-160.  doi: 10.3934/naco.2016005.  Google Scholar

[8] L. Ljungvist and T. J. Sargent, Recursive Macroeconomic Theory, The MIT Press, 2000.   Google Scholar
[9]

C. Malfatti, Memoria Sopra una Problema Stereotomico, Memoria di Matematica e di Fisica della Societa italiana della Scienze, 10 (1803), 235-244.   Google Scholar

[1]

Yasmine Cherfaoui, Mustapha Moulaï. Biobjective optimization over the efficient set of multiobjective integer programming problem. Journal of Industrial & Management Optimization, 2021, 17 (1) : 117-131. doi: 10.3934/jimo.2019102

[2]

Pablo Neme, Jorge Oviedo. A note on the lattice structure for matching markets via linear programming. Journal of Dynamics & Games, 2020  doi: 10.3934/jdg.2021001

[3]

Mahdi Karimi, Seyed Jafar Sadjadi. Optimization of a Multi-Item Inventory model for deteriorating items with capacity constraint using dynamic programming. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2021013

[4]

Ali Mahmoodirad, Harish Garg, Sadegh Niroomand. Solving fuzzy linear fractional set covering problem by a goal programming based solution approach. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2020162

[5]

Felix Finster, Jürg Fröhlich, Marco Oppio, Claudio F. Paganini. Causal fermion systems and the ETH approach to quantum theory. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020451

[6]

Kung-Ching Chang, Xuefeng Wang, Xie Wu. On the spectral theory of positive operators and PDE applications. Discrete & Continuous Dynamical Systems - A, 2020, 40 (6) : 3171-3200. doi: 10.3934/dcds.2020054

[7]

Yahia Zare Mehrjerdi. A new methodology for solving bi-criterion fractional stochastic programming. Numerical Algebra, Control & Optimization, 2020  doi: 10.3934/naco.2020054

[8]

Ke Su, Yumeng Lin, Chun Xu. A new adaptive method to nonlinear semi-infinite programming. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2021012

[9]

Tengfei Yan, Qunying Liu, Bowen Dou, Qing Li, Bowen Li. An adaptive dynamic programming method for torque ripple minimization of PMSM. Journal of Industrial & Management Optimization, 2021, 17 (2) : 827-839. doi: 10.3934/jimo.2019136

[10]

Min Xi, Wenyu Sun, Jun Chen. Survey of derivative-free optimization. Numerical Algebra, Control & Optimization, 2020, 10 (4) : 537-555. doi: 10.3934/naco.2020050

[11]

Pierre-Etienne Druet. A theory of generalised solutions for ideal gas mixtures with Maxwell-Stefan diffusion. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020458

[12]

Sergey Rashkovskiy. Hamilton-Jacobi theory for Hamiltonian and non-Hamiltonian systems. Journal of Geometric Mechanics, 2020, 12 (4) : 563-583. doi: 10.3934/jgm.2020024

[13]

Tuoc Phan, Grozdena Todorova, Borislav Yordanov. Existence uniqueness and regularity theory for elliptic equations with complex-valued potentials. Discrete & Continuous Dynamical Systems - A, 2021, 41 (3) : 1071-1099. doi: 10.3934/dcds.2020310

[14]

Juan Pablo Pinasco, Mauro Rodriguez Cartabia, Nicolas Saintier. Evolutionary game theory in mixed strategies: From microscopic interactions to kinetic equations. Kinetic & Related Models, 2021, 14 (1) : 115-148. doi: 10.3934/krm.2020051

[15]

Predrag S. Stanimirović, Branislav Ivanov, Haifeng Ma, Dijana Mosić. A survey of gradient methods for solving nonlinear optimization. Electronic Research Archive, 2020, 28 (4) : 1573-1624. doi: 10.3934/era.2020115

[16]

Xinpeng Wang, Bingo Wing-Kuen Ling, Wei-Chao Kuang, Zhijing Yang. Orthogonal intrinsic mode functions via optimization approach. Journal of Industrial & Management Optimization, 2021, 17 (1) : 51-66. doi: 10.3934/jimo.2019098

[17]

Wolfgang Riedl, Robert Baier, Matthias Gerdts. Optimization-based subdivision algorithm for reachable sets. Journal of Computational Dynamics, 2021, 8 (1) : 99-130. doi: 10.3934/jcd.2021005

[18]

Manxue You, Shengjie Li. Perturbation of Image and conjugate duality for vector optimization. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2020176

[19]

Marek Macák, Róbert Čunderlík, Karol Mikula, Zuzana Minarechová. Computational optimization in solving the geodetic boundary value problems. Discrete & Continuous Dynamical Systems - S, 2021, 14 (3) : 987-999. doi: 10.3934/dcdss.2020381

[20]

Claudianor O. Alves, Rodrigo C. M. Nemer, Sergio H. Monari Soares. The use of the Morse theory to estimate the number of nontrivial solutions of a nonlinear Schrödinger equation with a magnetic field. Communications on Pure & Applied Analysis, 2021, 20 (1) : 449-465. doi: 10.3934/cpaa.2020276

2019 Impact Factor: 1.366

Article outline

[Back to Top]