Strategic and Tactical Crude Oil Supply Chain: Mathematical Programming Models

Crude oil industry very fast became a strategic industry. Then, optimization of the Crude Oil Supply Chain (COSC) models has created new challenges. This fact motivated me to study the COSC mathematical programming models. We start with a systematic literature review to identify promising avenues. Afterwards, we elaborate three concert models to fill identified gaps in the COSC context, which are (i) joint venture formation, (ii) integrated upstream, and (iii) environmentally conscious design

Using stochastic model for lower financial risk management in refinery operation planning

Most Refineries historically models are deterministic, that is, they use nominal parameter values without taking into consideration the uncertainty in process, demands, refinery parameters, etc. And as a consequence, they are unable to perform risk management. In this paper a variety of methodologies for financial risk management in engineering decision have been already developed. We follow the approach presented by Barbaro and Bagajewicz (2004), who used two-stage stochastic programming model and you, can find all other approaches analyzed and discussed. The problem addressed here is that of determining the crude oil to purchase and decide on the production level of different products given predicts of demands. The profit is maximized taking into account revenues, crude oil costs, inventory costs, and lost demand costs. The model was tested using data from the Refinery owned by the State Oil Marketing Organization (SOMO) Company, Iraq. The results show that the stochastic model can forecast higher expected profit and lower risk compared to the deterministic model

Modelling and solution methods for stochastic optimisation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis we consider two research problems, namely, (i) language constructs for modelling stochastic programming (SP) problems and (ii) solution methods for processing instances of different classes of SP problems. We first describe a new design of an SP modelling system which provides greater extensibility and reuse. We implement this enhanced system and develop solver connections. We also investigate in detail the following important classes of SP problems: singlestage SP with risk constraints, two-stage linear and stochastic integer programming problems. We report improvements to solution methods for single-stage problems with second-order stochastic dominance constraints and two-stage SP problems. In both cases we use the level method as a regularisation mechanism. We also develop novel heuristic methods for stochastic integer programming based on variable neighbourhood search. We describe an algorithmic framework for implementing decomposition methods such as the L-shaped method within our SP solver system. Based on this framework we implement a number of established solution algorithms as well as a new regularisation method for stochastic linear programming. We compare the performance of these methods and their scale-up properties on an extensive set of benchmark problems. We also implement several solution methods for stochastic integer programming and report a computational study comparing their performance. The three solution methods, (a) processing of a single-stage problem with second-order stochastic dominance constraints, (b) regularisation by the level method for two-stage SP and (c) method for solving integer SP problems, are novel approaches and each of these makes a contribution to knowledge.Financial support was obtained from OptiRisk Systems

Optimización de un modelo de cadena de suministro en el sector de hidrocarburos mediante programación líneal estocástica

En el trabajo de grado se lleva a cabo una planeación de una red logística teórica del sector de hidrocarburos haciendo uso de programación lineal estocástica. Se usan algunos datos reales de la industria colombiana como referencia. Específicamente, se usa la metodología bi etapa para dar solución al problema planteado, y se llega a una planeación mensual donde se anuncian cuáles decisiones se deben tomar dentro de las operaciones de la red logística (producción de crudos, transporte, distribución) de manera que se maximice la ganancia esperada de la red. Finalmente, se lleva a cabo una comparación del uso de formulación estocástica versus un enfoque determinístico, de manera que se vislumbren las ganancias de tener en cuenta la aleatoriedad existente en el medio.On this graduation dissertation, a logistics planning is proposed for a theoretical supply chain network from the hydrocarbons sector, using a stochastic linear programming approach. Some real data from the Colombian industry is used as reference. To solve the proposed problem, a twostage methodology is applied, and the output of the analysis is a monthly planning for the supply chain basic operations (production, transportation and distribution) that maximizes the expected profit. Finally, the stochastic approach is compared to the deterministic approach (usually applied in real hydrocarbon companies) in order to visualize the benefits of including randomness to the overall analysis.Ingeniero (a) IndustrialPregrad