Description
Thesis examination.Abstract:
This PhD thesis has as objective to investigate uncertainty in the decision-making processes within the tactical and operational planning of the downstream oil network. In this direction, this work implements decision-support tools based on mathematical programming techniques, comprising linear programming (LP), mixed-integer linear programming (MILP), stochastic programming (SP) and robust optimization (RO), besides incorporating market demands and prices as random parameters. Therefore, stochastic programming models and robust optimization models are introduced and studied within the downstream oil supply chain (DOSC) context. Other methodologies are investigated and employed to deal with issues related with uncertainty, namely time series analysis, scenario tree analysis, scenario reduction algorithms and Monte Carlo simulation. A real-world case study based on Portuguese oil industry is presented and explored through the developed mathematical programming models.
| Period | 2018 |
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| Examination held at |
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| Degree of Recognition | International |