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What is Stochastic Programming

Handbook of Research on Artificial Intelligence Techniques and Algorithms
To design for whatever scenario of the product life cycle, the optimal supply chain network.
Published in Chapter:
A Stochastic Approach to Product-Driven Supply Chain Design
Khaoula Besbes (Université Lillle Nord de France, France & Université de Sfax, Tunisia), Hamid Allaoui (Université Lillle Nord de France, France), Gilles Goncalves (Université Lillle Nord de France, France), and Taicir Loukil (Université de Sfax, Tunisia)
DOI: 10.4018/978-1-4666-7258-1.ch003
Abstract
Supply chain is an alliance of independent business processes, such as supplier, manufacturing, and distribution processes that perform the critical functions in the order fulfillment process. However, the discussions in marketing and logistic literature universally conclude that it would be desirable to determine the life cycle of products in the firm, as they have a great impact on appropriate supply chain design. Designing a supply chain effectively is a complex and challenging task, due to the increasing outsourcing, globalization of businesses, continuous advances in information technology, and product life cycle uncertainty. Indeed, uncertainty is one of the characteristics of the product life cycle. In particular, the strategic design of the supply chain has to take uncertain information into account. This chapter presents a two-phase mathematical programming approach for effective supply chain design with product life cycle uncertainty considerations.
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More Results
Stochastic Logistics Network Design with Deadlines
Stochastic programming is a framework for modeling optimization problems that involve uncertainty. Stochastic programming models are similar in style but take advantage of the fact that probability distributions governing the data are known or can be estimated. The goal here is to find some policy that is feasible for the possible data instances and maximizes the expectation of some function of the decisions and the random variables ( http://en.wikipedia.org/wiki/Stochastic_programming ).
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Solving Solid Transportation Problems with Multi-Choice Cost and Stochastic Supply and Demand
Stochastic programming is a framework for modeling optimization problems that involve uncertainty.
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GA Based FGP for Resource Allocation in Farming
Stochastic programming is an optimization technique for solving problems with probabilistically defined uncertain data.
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Genetic Algorithm for FGP Model of a Multiobjective Bilevel Programming Problem in Uncertain Environment
In a certain programming environment, the model parameters are found to be random in nature (i.e., not exact) and certain probability distributions of occurrence of various events are considered in modeling and solving problems in an uncertain environment.
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Stochastic Programming and Value Based Decisions
Subfield of mathematical programming that considers optimization in the presence of uncertainty.
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FGP for Chance Constrained Fractional MODM Problem
In a certain programming environment, model parameters are random in nature and probabilities of occurrence of various events are considered there in modeling and solving problems.
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FGP Model for Emission-Economic Power Dispatch
Stochastic programming is an optimization technique for solving problems with uncertain data, where probability distributions of model parameters are involved in a decision environment.
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A Genetic Algorithm to Goal Programming Model for Crop Production with Interval Data Uncertainty
Stochastic programming is an optimization technique for solving problems with probabilistically defined data in uncertain environment.
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Value Based Decision Control for Complex Systems
The subfield of mathematical programming that considers optimization in the presence of uncertainty.
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Preferences, Utility, and Stochastic Approximation
Subfield of mathematical programming that considers optimization in the presence of uncertainty.
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Preferences, Utility, and Stochastic Approximation
Subfield of mathematical programming that considers optimization in the presence of uncertainty.
Full Text Chapter Download: US $37.50 Add to Cart
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