Document Type

Thesis

Date of Degree Completion

Spring 2020

Degree Name

Master of Science (MS)

Department

Computational Science

Committee Chair

Donald Davendra

Second Committee Member

Razvan Andonie

Third Committee Member

Szilárd Vajda

Abstract

Pollution is a major environmental issue around the world. Despite the growing use and impact of commercial vehicles, recent research has been conducted with minimizing pollution as the primary objective to be reduced. The objective of this project is to implement different optimization algorithms to solve this problem. A basic model is created using the Vehicle Routing Problem (VRP) which is further extended to the Pollution Routing Problem (PRP). The basic model is updated using a Monte Carlo Algorithm (MCA). The data set contains 180 data files with a combination of 10, 15, 20, 25, 50, 75, 100, 150, and 200 groups of cities. The optimizing techniques applied are the Discrete Differential Evolution (DDE) and, Discrete Particle Swarm Optimization (DPSO) with a Python Tkinter frontend. The objectives to be optimized are the fuel consumption rate and distance traveled and a statistical comparison is done between the different algorithm to compare effectiveness.

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