Document Type

Thesis

Degree

Master of Science (MS)

Department

Mechanical Engineering

First Advisor's Name

George Dulikravich

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Igor Tsukanov

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Leonel Lagos

Third Advisor's Committee Title

Committee Member

Keywords

hybrid optimization, differential evolution, pipeline, transient, method of characteristics

Date of Defense

2014

Abstract

The effectiveness of an optimization algorithm can be reduced to its ability to navigate an objective function’s topology. Hybrid optimization algorithms combine various optimization algorithms using a single meta-heuristic so that the hybrid algorithm is more robust, computationally efficient, and/or accurate than the individual algorithms it is made of. This thesis proposes a novel meta-heuristic that uses search vectors to select the constituent algorithm that is appropriate for a given objective function. The hybrid is shown to perform competitively against several existing hybrid and non-hybrid optimization algorithms over a set of three hundred test cases. This thesis also proposes a general framework for evaluating the effectiveness of hybrid optimization algorithms. Finally, this thesis presents an improved Method of Characteristics Code with novel boundary conditions, which better characterizes pipelines than previous codes. This code is coupled with the hybrid optimization algorithm in order to optimize the operation of real-world piston pumps.

Identifier

FI14110709

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