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A Multi-Period Stochastic Location-Inventory Problem
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| 3.18 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
A two-stage stochastic linear programming model is proposed to formulate the Multi-Period Stochastic Location-Inventory Problem, where both location, allocation and inventory management related decisions are considered. A variant, which adds the concept of lead times between suppliers and DCs, is also
formulated as a two-stage stochastic linear programming model.
In order to solve it, the concept of demand scenarios is introduced as a means to capture the uncertainty of the customers’ demand. This way, the Multi-Period Stochastic Location-Inventory Problem can
be formulated as a mixed-integer linear programming model. This is the model that needs to be solved,
which can be done, for example, through the use of a commercial solver.
A set of instances is computationally generated for the purpose of performing computational tests.
Afterwards, two batches of computational tests are run. The first batch uses the generated instances as
they are, while in the second batch those instances have their fixed costs for locating a DC at some site
modified (the original values are multiplied by one hundred).
Some characteristics and metrics are chosen in an effort to evaluate the quality of the solving approach. Most instances are solved in a considered suitable time (the majority take less than a minute).
Only a few (the largest ones in both number of decision variables and constraints) are not solved due to
hardware constraints.
Descrição
Tese de mestrado, Estatística e Investigação Operacional (Investigação Operacional), 2023, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
location-inventory procura estocástica multi-período two-stage stochastic linear programming Teses de mestrado - 2023