Modeling supply contracts in production planning with disjunctive programming
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Perustieteiden korkeakoulu |
Master's thesis
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Authors
Date
2023-12-12
Department
Major/Subject
Systems and Operations Research
Mcode
SCI3055
Degree programme
Master’s Programme in Mathematics and Operations Research
Language
en
Pages
40+1
Series
Abstract
This thesis aims to demonstrate how disjunctive programming can be used to model raw material procurement contracts in the context of a two-stage stochastic mixed integer linear programming (MILP) production planning problem. We will see that disjunctive programming provides an efficient framework for defining the constraints needed to model raw material procurement contracts. More specifically, we will analyze a simple two-stage stochastic production planning model where first-stage variables represent decisions regarding contracts and second-stage variables correspond to production planning decisions. We conclude the advantage of implementing the stochastic model is not as great as we initially thought. Namely, the Value of the Stochastic Solution (VSS) was lower then expected. Aside from this, the literature review in this area suggests most existing works are concerned with industry specific applications. Hence, our other goal is to introduce an example application that is easier to understand than the more sophisticated application-specific works available in the literature. The model is implemented using Julia programming language and makes use of the DisjunctiveProgramming.jl library. Overall, we concluded that disjunctive programming is a useful framework that can simplify and expedite the modeling process by providing a higher level of abstraction. However, there is still quite a bit of work to be done on scalability and performance if these types of models are to be deployed in the industry.Description
Supervisor
Oliveira, FabrícioThesis advisor
Belyak, NikitaKeywords
linear programming, MILP, disjunctive programming, supply chain optimisation