Date of Award
8-2012
Culminating Project Type
Starred Paper
Degree Name
Engineering: M.E.M
Department
Mechanical and Manufacturing Engineering
College
College of Science and Engineering
First Advisor
Ben Baliga
Second Advisor
Hiral Shah
Third Advisor
Balsy Kasi
Keywords and Subject Headings
Genetic, Algorithm, Inventory, Level Planning, Optimization
Abstract
While genetic algorithms have been explored academically, and in at least two known cases, commercialized, they still seem to be an underutilized technique for solving engineering management problems. One of the reasons for this is the general lack of awareness and understanding about genetic algorithms. Another reason is that genetic algorithms have generally been viewed as being too costly in terms of computing resources to implement for complex problems. This paper examines an example management problem and an example genetic algorithm that was developed to solve it in order to illustrate the applicability of such algorithms to similar or more complex management problems. In an experiment described in this paper, a Java-based genetic algorithm package was used to implement an evolutionary process for finding optimal solutions to a selected aggregate planning problem. The performance and results of the process were compared to solutions to the same problem found using manual and non-evolutionary automated techniques. The results found using the experimental evolutionary process surpassed those obtained by the other techniques, both in terms of speed and optimization.
Recommended Citation
Gerhart, Robert, "Utilization of Evolutionary Algorithms to Improve Engineering Decision - Making" (2012). Culminating Projects in Mechanical and Manufacturing Engineering. 74.
https://repository.stcloudstate.edu/mme_etds/74
Comments/Acknowledgements
I would like to thank Dr. Ben Baliga for his leadership in the Master of Engineering Management program, and for his guidance with this paper. Without his encouragement, I probably would not have known about or enroll (much less complete) this unique program.
I would like to thank the Graduate Faculty (Dr. Ben Baliga, Dr. Hirai Shah, and Dr. Balsy Kasi) for their time, consideration, and valuable feedback during this process.
I would like to thank J. Richard Soderberg and anonymous other coworkers for inspiring me to return to school as part of my ongoing quest for self-actualization. You revealed to me, with perfect clarity, the doors through which I needed to pass next in order to continue my personal journey.
I would like to thank everybody else in my cohort. This could have been a long and tedious gauntlet; but each and every one of you helped make our class sessions not only informative but outright entertaining. As much as I am ready to be done, part of me will really miss my semi-weekly equal dose of humor and good-natured mutual abuse.
I would like to thank Rick Bernett for his instruction in Operations Management, and for taking the time to help me better understand the scope and objectives of my capstone project. Prior to obtaining his advice, I had no idea where to direct my efforts.
Saving the best for last, I would like to thank my loving wife, Tiffany, and my kids: Heather, Lisa, Breanna, and Alyx. It is because of all of you that I started this program, and if it were not for your sacrifices, I would not likely have been able to finish the program or this paper. Not only did Tiffany endure many nights of solo parenting so I could disappear into my "cave" to study, but she even put the pursuit of her own long-delayed degree on hold so I could focus on finishing mine. I love you all more than you will ever realize.