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Modeling and comparative analysis of a stochastic production planning system with demand uncertainty

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Modeling and comparative analysis of a stochastic production planning system with demand uncertainty

Vineet, Vibhor (2006) Modeling and comparative analysis of a stochastic production planning system with demand uncertainty. Masters thesis, Concordia University.

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Abstract

Effective planning strategies are essential to minimize high costs of production and inventory. Uncertainty and seasonal variation in product demand is a major issue that contributes to a substantial share of production planning costs. Hence, it is important to consider the uncertain information while designing a production planning model. This thesis is aimed at presenting a comparative analysis of deterministic and stochastic approaches towards finding optimal solutions for demand uncertainty problems. The first model is a generic mixed-integer programming model to maximize total profit. Decision variables are identified and random values are substituted by their expected values considering uncertainty to obtain the expected value solutions. Second model is formulated as a stochastic programming model by adding scenarios and probabilities in the deterministic model to explicitly account for the uncertainties in the product demand. The models are programmed and solved by LINGO optimization solver based on data collected from a brewing company. Several test problems are solved by varying the input parameters, product demand and probability of existence of scenarios to study the sensitivity of the models. A statistical comparative analysis is conducted on all the example problems by measuring the Expected Value of Perfect Information (EVPI), Value of Stochastic Solution (VSS) and the results are discussed.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Vineet, Vibhor
Pagination:x, 117 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Date:2006
Thesis Supervisor(s):Chen, Ming Yuan
Identification Number:LE 3 C66M43M 2006 V56
ID Code:9064
Deposited By: Concordia University Library
Deposited On:18 Aug 2011 18:43
Last Modified:13 Jul 2020 20:05
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