This dissertation solves an optimization problem in the area of scheduling large-scale
petroleum development projects under several resources constraints. The dissertation
focuses on the application of a metaheuristic search Genetic Algorithm (GA) in solving
the problem. The GA is a global search method inspired by natural evolution. The
method is widely applied to solve complex and sizable problems that are difficult to
solve using exact optimization methods. A classical resource allocation problem in
operations research known under Knapsack Problems (KP) is considered for the
formulation of the problem.
Motivation of the present work was initiated by certain petroleum development
scheduling problem in which large-scale investment projects are to be selected subject to
a number of resources constraints in several periods. The constraints may occur from
limitations in various resources such as capital budgets, operating budgets, and drilling
rigs. The model also accounts for a number of assumptions and business rules encountered in the application that motivated this work. The model uses an economic
performance objective to maximize the sum of Net Present Value (NPV) of selected
projects over a planning horizon subject to constraints involving discrete time dependent
variables.
Computational experiments of 30 projects illustrate the performance of the model.
The application example is only illustrative of the model and does not reveal real data. A
Greedy algorithm was first utilized to construct an initial estimate of the objective
function. GA was implemented to improve the solution and investigate resources
constraints and their effect on the assets value.
The timing and order of investment decisions under constraints have the prominent
effect on the economic performance of the assets. The application of an integrated
optimization model provides means to maximize the financial value of the assets,
efficiently allocate limited resources and to analyze more scheduling alternatives in less
time.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-3218 |
| Date | 15 May 2009 |
| Creators | Husni, Mohammed Hamza |
| Contributors | Startzman, Richard A. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
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