• Title/Summary/Keyword: Stochastic Orders

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On Some New Stochastic Orders of Interest in Reliability Theory

  • Kayid, M.;El-Bassiouny, A.H.;Al-Wasel, I.A.
    • International Journal of Reliability and Applications
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    • v.8 no.1
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    • pp.95-109
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    • 2007
  • The purpose of this paper is to study new notions of stochastic comparisons and ageing classes based on the total time on test transform order. We give relationships to other stochastic orders and aging classes given previously. Several preservation properties under the reliability operations of random minima and series system are given.

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A Note on the Stochastic Comparison in Production Yield Management (생산 수율 관리 문제와 확률적 비교)

  • Park, Kyungchul
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.5
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    • pp.477-480
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    • 2014
  • The single-period production inventory control problem under random yield is considered to analyze the impact of the yield characteristics on the firm's profit. We use the stochastic comparison as a main vehicle to compare the profits resulted under different random yields. Commonly used stochastic orderings are addressed with an analysis of their implications on the firm's profit. Moreover, a distribution-free bound on the profit is derived.

Testing of Stochastic Trends, Seasonal and Cyclical Components in Macroeconomil Time Series

  • Gil-Alana Luis A.
    • Communications for Statistical Applications and Methods
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    • v.12 no.1
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    • pp.101-115
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    • 2005
  • We propose in this article a procedure for testing unit and fractional orders of integration, with the roots simultaneously occurring in the trend, the seasonal and the cyclical component of the time series. The tests have standard null and local limit distributions. However, finite sample critical values are computed, and several Monte Carlo experiments conducted across the paper show that the rejection frequencies against unit (and fractional) orders of integration are relatively high in all cases. The tests are applied to the UK consumption and income series, the results showing the importance of the roots corresponding to the trend and the seasonal components and, though the unit roots are found to be fairly suitable models, we show that fractional processes (including one for the cyclical component) may also be plausible alternatives in some cases.

ROBUST PORTFOLIO OPTIMIZATION UNDER HYBRID CEV AND STOCHASTIC VOLATILITY

  • Cao, Jiling;Peng, Beidi;Zhang, Wenjun
    • Journal of the Korean Mathematical Society
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    • v.59 no.6
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    • pp.1153-1170
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    • 2022
  • In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

Robust adaptive IMC controller for a class of nonminimum phase stochastic systems (비최소 위상 확률 시스템을 대상으로 한 견실한 적응 IMC 제어기)

  • 최종호;김호찬
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.139-144
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    • 1993
  • In this paper, a robust reduced order adaptive controller is proposed based on Internal Model Control(IMC) structure for stochastic linear stable systems. The concept of gain margin is utilized to make the adaptive IMC controller robust. We prove the stability of the proposed adaptive IMC system for stable plants under the assumption that upper bounds for system orders are known. Simulation results show that the proposed method has good performance and stability robustness.

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STOCHASTIC ORDERS IN RETRIAL QUEUES AND THEIR APPLICATIONS

  • Shin Yang Woo
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.105-108
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    • 2000
  • We consider a Markovian retrial queue with waiting space in which the service rates and retrial rates depend on the number of customers in the service facility and in the orbit, respectively. Each arriving customer from outside or orbit decide either to enter the facility or to join the orbit in Bernoulli manner whose entering probability depend on the number of customers in the service facility. In this paper, a stochastic order relation between two bivariate processes (C(t), N(t)) representing the number of customers C(t) in the service facility and N(t) one in the orbit is deduced in terms of corresponding parameters by constructing the equivalent processes on a common probability space. Some applications of the results to the stochastic bounds of the multi-server retrial model are presented.

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Walking load model for single footfall trace in three dimensions based on gait experiment

  • Peng, Yixin;Chen, Jun;Ding, Guo
    • Structural Engineering and Mechanics
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    • v.54 no.5
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    • pp.937-953
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    • 2015
  • This paper investigates the load model for single footfall trace of human walking. A large amount of single person walking load tests were conducted using the three-dimensional gait analysis system. Based on the experimental data, Fourier series functions were adopted to model single footfall trace in three directions, i.e. along walking direction, direction perpendicular to the walking path and vertical direction. Function parameters such as trace duration time, number of Fourier series orders, dynamic load factors (DLFs) and phase angles were determined from the experimental records. Stochastic models were then suggested by treating walking rates, duration time and DLFs as independent random variables, whose probability density functions were obtained from experimental data. Simulation procedures using the stochastic models are presented with examples. The simulated single footfall traces are similar to the experimental records.

A Generalized Finite Difference Method for Solving Fokker-Planck-Kolmogorov Equations

  • Zhao, Li;Yun, Gun Jin
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.4
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    • pp.816-826
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    • 2017
  • In this paper, a generalized discretization scheme is proposed that can derive general-order finite difference equations representing the joint probability density function of dynamic response of stochastic systems. The various order of finite difference equations are applied to solutions of the Fokker-Planck-Kolmogorov (FPK) equation. The finite difference equations derived by the proposed method can greatly increase accuracy even at the tail parts of the probability density function, giving accurate reliability estimations. Compared with exact solutions and finite element solutions, the generalized finite difference method showed increasing accuracy as the order increases. With the proposed method, it is allowed to use different orders and types (i.e. forward, central or backward) of discretization in the finite difference method to solve FPK and other partial differential equations in various engineering fields having requirements of accuracy or specific boundary conditions.

Determination of Economic Inventory Quantity under Probabilistic Demands and Cancellation of Orders in Production System with Two Different Production Speeds (이중생산속도를 가지는 생산시스템에서 확률적인 수요와 주문취소를 고려한 경제적 재고량 결정)

  • Lim, Si Yeong;Hur, Sun;Park, You-Jin
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.3
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    • pp.313-320
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    • 2014
  • We consider the problem to find economic inventory quantity of a single commodity under stochastic demands and order cancellation. In contrast to the traditional economic production quantity (EPQ) model, we assume that once the amount of inventory reaches to a predetermined level of quantity then the production is not halted but its production speed decreases until the inventory level drops to zero. We establish two probabilistic models representing the behaviors of both the high-production period and low-production period, respectively, and derive the relationship between the level of inventory and costs of production, cancellation, and holding, from which the quantity of economic inventory is obtained.

Genetic Algorithm-Based Coordinated Replenishment in Multi-Item Inventory Control

  • Nagasawa, Keisuke;Irohara, Takashi;Matoba, Yosuke;Liu, Shuling
    • Industrial Engineering and Management Systems
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    • v.12 no.3
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    • pp.172-180
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    • 2013
  • We herein consider a stochastic multi-item inventory management problem in which a warehouse sells multiple items with stochastic demand and periodic replenishment from a supplier. Inventory management requires the timing and amounts of orders to be determined. For inventory replenishment, trucks of finite capacity are available. Most inventory management models consider either a single item or assume that multiple items are ordered independently, and whether there is sufficient space in trucks. The order cost is commonly calculated based on the number of carriers and the usage fees of carriers. In this situation, we can reduce future shipments by supplementing items to an order, even if the item is not scheduled to be ordered. On the other hand, we can reduce the average number of items in storage by reducing the order volume and at the risk of running out of stock. The primary variables of interest in the present research are the average number of items in storage, the stock-out volume, and the number of carriers used. We formulate this problem as a multi-objective optimization problem. In a numerical experiment based on actual shipment data, we consider the item shipping characteristics and simulate the warehouse replenishing items coordinately. The results of the simulation indicate that applying a conventional ordering policy individually will not provide effective inventory management.