Simulation of an Invetory Model by Stochastic Differential Equation Using sw Mathematica

被引:0
|
作者
Lukas, Ladislav [1 ]
机构
[1] Univ West Bohemia, Fac Econ, Dept Econ & Quantitat Methods, Univ 22, Plzen 30614, Czech Republic
关键词
stochastic dynamic inventory model; replenishment process; stochastic demand; stochastic differential equation; sample mean process; numerical simulation in Mathematica; LEVEL-DEPENDENT DEMAND;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
The paper deals with stochastic dynamic inventory models which are solved numerically. An area of inventory theory research that has recently been receiving considerable attention involves situations in which the demand rate is dependent on the level of inventory. Inventory for an item is replenished by a time dependent deterministic process, in the simples case, with constant rate one. Simultaneously, the product under inventory is depleted by stochastic demand which rate depends upon the current inventory level. Stochastic differential equation of Ito type for the inventory level is formulated and used for numerical computations. All simulated paths of inventory levels are generated by our Mathematica code. Sample mean path is calculated thereof and further filtered in order to get some inventory management important values. Two main Mathematica commands for generation stochastic processes is presented, too.
引用
收藏
页码:357 / 363
页数:7
相关论文
共 50 条
  • [1] A STOCHASTIC SIMULATION OF ORDINARY DIFFERENTIAL EQUATION SYSTEMS
    MULLER, KH
    ELECTRONISCHE DATENVERARBEITUNG, 1969, 11 (11): : 533 - &
  • [2] Computation and simulation of langevin stochastic differential equation
    Ahangar, Reza
    Journal of Combinatorial Mathematics and Combinatorial Computing, 2013, 86 : 183 - 198
  • [3] A Stochastic Differential Equation Inventory Model
    Tsoularis A.
    International Journal of Applied and Computational Mathematics, 2019, 5 (1)
  • [4] Vulnerability Discovery Model for a Software System Using Stochastic Differential Equation
    Shrivastava, A. K.
    Sharma, Ruchi
    Kapur, P. K.
    2015 1ST INTERNATIONAL CONFERENCE ON FUTURISTIC TRENDS ON COMPUTATIONAL ANALYSIS AND KNOWLEDGE MANAGEMENT (ABLAZE), 2015, : 199 - 205
  • [5] Monte-Carlo simulation of a stochastic differential equation
    Arif ULLAH
    Majid KHAN
    M KAMRAN
    R KHAN
    盛正卯
    Plasma Science and Technology, 2017, 19 (12) : 10 - 18
  • [6] Monte-Carlo simulation of a stochastic differential equation
    Arif ULLAH
    Majid KHAN
    M KAMRAN
    R KHAN
    盛正卯
    Plasma Science and Technology, 2017, (12) : 10 - 18
  • [7] Monte-Carlo simulation of a stochastic differential equation
    Ullah, Arif
    Khan, Majid
    Kamran, M.
    Khan, R.
    Sheng, Zhengmao
    PLASMA SCIENCE & TECHNOLOGY, 2017, 19 (12)
  • [8] A stochastic differential equation model for pest management
    Xuewen Tan
    Sanyi Tang
    Xiaozhou Chen
    Lianglin Xiong
    Xinzhi Liu
    Advances in Difference Equations, 2017
  • [9] A STOCHASTIC DIFFERENTIAL EQUATION SIS EPIDEMIC MODEL
    Gray, A.
    Greenhalgh, D.
    Hu, L.
    Mao, X.
    Pan, J.
    SIAM JOURNAL ON APPLIED MATHEMATICS, 2011, 71 (03) : 876 - 902
  • [10] Stochastic Differential Equation Model to Prendiville Processes
    Granita
    Bahar, Arifah
    22ND NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM22), 2015, 1682