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dc.date.accessioned2022-04-14T09:58:34Z-
dc.date.available2022-04-14T09:58:34Z-
dc.date.issued2015-
dc.identifier.citationFarrugia, L. (2015). Theory of stochastic integer programming with applications (Bachelor's dissertation).en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/93788-
dc.descriptionB.SC.(HONS)STATS.&OP.RESEARCHen_GB
dc.description.abstractIn this thesis we shall present the theory of Integer Stochastic Programming. We shall start by giving a short summary on standard Stochastic Linear Programming theory since most of the theory is its continuation. Several properties of the second-stage value function shall be discussed. Most notably the hurdles encountered when integrality is introduced to the second-stage value function. Additionally, Simple Integer Recourse shall be discussed so that it can be used to solve problems with simple recourse. We shall also present an algorithm named Integer L-Shaped Method. Note that this algorithm is a continuation of the Standard L-Shaped method but contains stronger cuts by using the Branch and Cut technique, a technique specifically made for two-staged integer stochastic programs. After these theoretical results, we continue on with the application section of the thesis. The main purpose of this part is to use as much previously discussed theory as possible to solve stochastic mixed or pure integer problems. We are given two problems, the Farmer's Problem and the Kiosk Owner problem. The farmer's problem will be solved by using the Integer L-shaped algorithm while the Kiosk Owner problem shall be solved by using Simple Integer Recourse theory.en_GB
dc.language.isoenen_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectStochastic programmingen_GB
dc.subjectLinear programmingen_GB
dc.subjectOperations researchen_GB
dc.titleTheory of stochastic integer programming with applicationsen_GB
dc.typebachelorThesisen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.publisher.institutionUniversity of Maltaen_GB
dc.publisher.departmentFaculty of Science. Department of Statistics and Operations Researchen_GB
dc.description.reviewedN/Aen_GB
dc.contributor.creatorFarrugia, Lucas (2015)-
Appears in Collections:Dissertations - FacSci - 2015
Dissertations - FacSciSOR - 2015

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