Date of Thesis

Spring 2024

Description

This thesis investigates the previously unstudied Precedence-Constrained Quadratic Knapsack Problem (PC-QKP), an NP-hard nonlinear combinatorial optimization problem. The PC-QKP is a variation of the traditional Knapsack Problem (KP) that introduces several additional complexities. By developing custom exact and approximate solution methods, and testing these on a wide range of carefully structured PC-QKP problem instances, we seek to identify and understand patterns that make some cases easier or harder to solve than others. The findings aim to help develop better strategies for solving this and similar problems in the future.

Keywords

Combinatorial Optimization, Knapsack Problem, Nonlinear Optimization, Operations Research, Heuristic, Linearization

Access Type

Honors Thesis

Degree Type

Bachelor of Science

Major

Applied Mathematical Sciences

Second Major

Computer Science

Minor, Emphasis, or Concentration

Computer Science

First Advisor

Lucas Waddell

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