• Title/Summary/Keyword: random demand

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AN EOQ MODEL FOR DETERIORATING INVENTORY WITH ALTERNATING DEMAND RATES

  • A.K. Pal;B. Mabdal
    • Journal of applied mathematics & informatics
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    • v.4 no.2
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    • pp.457-468
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    • 1997
  • The present paper deals with an economic order quan-tity model for items deteriorating at some constant rate with demand changing at a known and at a random point of time in the fixed pro-duction cycle.

Fuzzy Random Facility Location Problems

  • Ishii, Hiroaki;Itoh, Takeshi;Katagiri, Hideki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.663-665
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    • 1998
  • This paper investigates a facility location problem where there are possible demand points with demand occuring probabilites and actual distances between these points and the facility site to be determined are ambiguous, Further we define the fuzzy goal with respect to the maximum value among the actual distances between demand points and the facility. We determine the site of facility maximizing the minimal satisficing degree under the chance constraint. We propose the geometric algorithm to find this optimal site.

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A Study on Dynamic Lot Sizing Problem with Random Demand (확률적 수요를 갖는 단일설비 다종제품의 동적 생산계획에 관한 연구)

  • Kim, Chang Hyun
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.3
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    • pp.194-200
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    • 2005
  • A stochastic dynamic lot sizing problem for multi-item is suggested in the case that the distribution of the cumulative demand is known over finite planning horizons and all unsatisfied demand is fully backlogged. Each item is produced simultaneously at a variable ratio of input resources employed whenever setup is incurred. A dynamic programming algorithm is proposed to find the optimal production policy, which resembles the Wagner-Whitin algorithm for the deterministic case problem but with some additional feasibility constraints.

Integrating Random Network Coding with On-Demand Multicast Routing Protocol

  • Park, Joon-Sang;Baek, Seung Jun
    • ETRI Journal
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    • v.34 no.5
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    • pp.775-778
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    • 2012
  • We propose integrating random network coding with the Enhanced On-Demand Multicast Routing Protocol (E-ODMRP). With the Network Coded E-ODMRP (NCE-ODMRP), we present a framework that enables a seamless integration of random linear network coding with conventional ad hoc multicast protocols for enhanced reliability. Simulation results show that the NCE-ODMRP achieves a nearly perfect packet delivery ratio while keeping the route maintenance overhead low to a degree similar to that of the E-ODMRP.

Robust Newsvendor Model With Random Yield and Customer Balking (불확실한 수율과 고객이탈행위를 고려한 강건한 뉴스벤더 모델)

  • Jung, Uk;Lee, Se Won
    • Journal of Korean Society for Quality Management
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    • v.40 no.4
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    • pp.441-452
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    • 2012
  • Purpose: In this paper, we have considered a problem of newsvendor model in an environment of random yields in quality and customer balking behavior, in which only the mean and the variance of the demand are known. In practice, the distributional information of the demand is very limited and only the mean and variance are guessed by experience. In addition, due to the customers balking behavior occurring when the available inventory level decreases, the product's demand becomes a function of inventory level so that the classical newsvendor's optimal order quantity is no longer optimal. Methods: We have developed an optimal order quantity model that enables us to incorporate the random yield of a product and the customer balking information such as a threshold inventory level of balking and the corresponding probability of a sale during the balking. Results: We illustrated the concepts developed here through simple numerical examples and showed the robustness of our model in a various setting of parameters. Conclusion: This paper provides a useful analysis showing that our distribution-specific and distribution-free approach to the optimal order quantity in the newsboy model can act as an effective tools to match supply with demand for these product lines.

Parametric study on probabilistic local seismic demand of IBBC connection using finite element reliability method

  • Taherinasab, Mohammad;Aghakouchak, Ali A.
    • Steel and Composite Structures
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    • v.37 no.2
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    • pp.151-173
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    • 2020
  • This paper aims to probabilistically evaluate performance of two types of I beam to box column (IBBC) connection. With the objective of considering the variability of seismic loading demand, statistical features of the inter-story drift ratio corresponding to the second, fifth and eleventh story of a 12-story steel special moment resisting frames are extracted through incremental dynamic analysis at global collapse state. Variability of geometrical variables and material strength are also taken into account. All of these random variables are exported as inputs to a probabilistic finite element model which simulates the connection. At the end, cumulative distribution functions of local seismic demand for each component of each connection are provided using histogram sampling. Through a parametric study on probabilistic local seismic demand, the influence of some geometrical random variables on the performance of IBBC connections is demonstrated. Furthermore, the probabilistic study revealed that IBBC connection with widened flange has a better performance than the un-widened flange. Also, a design procedure is proposed for WF connections to achieve a same connection performance in different stories.

Prediction of Global Industrial Water Demand using Machine Learning

  • Panda, Manas Ranjan;Kim, Yeonjoo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.156-156
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    • 2022
  • Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

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Estimation of diesel fuel demand function using panel data (시도별 패널데이터를 이용한 경유제품 수요함수 추정)

  • Lim, Chansu
    • Journal of Energy Engineering
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    • v.26 no.2
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    • pp.80-92
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    • 2017
  • This paper attempts to estimate the diesel fuel demand function in Korea using panel data panel data of 16 major cities or provinces which consist of diesel demands, diesel market prices and gross value added from the year 1998 to 2015. I apply panel GLS(generalized least square) model, fixed effect model, random effect model and dynamic panel model to estimating the parameters of the diesel fuel demand function. The results show that short-run price elasticities of the diesel fuel demand are estimated to be -0.2146(panel GLS), -0.2886(fixed effect), -0.2854(random effect), -0.1905(dynamic panel) respectively. And short-run income elasticities of the diesel fuel demand are estimated to be 0.7379(panel GLS), 0.4119(fixed effect), 0.7260(random effect), 0.4166(dynamic panel) respectively. The short-run price and income elasticities explain that demand for diesel fuel is price- and income-inelastic. The long-run price and income elasticities are estimated to be -0.4784, 1.0461 by dynamic panel model, which means that demand for diesel fuel is price-inelastic but income-elastic in the long run. In addition I apply dummy variable model to estimate the effect of 16 major cities or provinces on diesel demands. The results show that diesel demands is affected 10 regions on the basis of Seoul.

A Continuous Review(s, S) Inventory Model in which Depletion is Due to Demand and Loss of Units

  • Choi, Jin-Yeong;Kim, Man-Sik
    • Journal of Korean Institute of Industrial Engineers
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    • v.11 no.1
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    • pp.33-39
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    • 1985
  • A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between successive unit demands, as well as those between successive unit losses are independently and identically distributed random variables having negative exponential distribution with respective parameters. We have derived the steady state probability distribution of the stock level assuming instantaneous delivery of order under (s, S) inventory policy. Also we have derived total expected cost expression and the necessary conditions to be satisfied for an optimal solution.

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Allocation of aircraft under demand by Wets' approach to stochastic programs with simple recourse

  • Sung, Chang-Sup
    • Journal of the Korean Operations Research and Management Science Society
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    • v.4 no.1
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    • pp.59-64
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    • 1979
  • The application of optimization techniques to the planning of industrial, economic, administrative and military activities with random technological coefficients has been extensively studied in the literature. Stochastic (linear) programs with simple recourse essentially model the allocation of scarce resources under uncertainty with linear penalties associated with shortages or surplus. This work on a problem with a discrete random resource vector, "The allocation of aircraft under uncertain demand" given in (1), is easily and efficiently handled by the application of the recently developed Wets' algorithm (8) for solving stochastic programs with simple recourse, which approves that such class of stochastic problems can be solved with the same efficiency as solving linear programs of the same size. It is known that the algorithm is also applicable to stochastic programs with continuous random demands for their approximate solutions.

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