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Integration of genetic algorithms to engineering optimization problems

Tsai, Jay-Shinn
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1176310901

Abstract Details

1993, Master of Science (MS), Ohio University, Industrial and Manufacturing Systems Engineering (Engineering).
Genetic algorithms (GAs) and their integration with traditional operations have been utilized for solving a variety of optimization problems in engineering. A real- valued code genetic algorithm with stochastic multi-criteria was utilized to solve the decision making of three engineering optimization problems: the Exclusive-OR (XOR) problem, the inverse kinematics problem for robots with multiple degrees of freedom, and the job shop scheduling (JSS) problem. Minimizing RMS error (Root Mean Square Error), arm positioning error with joint angle displacements, and the combination of maximum flow time, mean flow time, maximum tardiness, mean tardiness, work-in process inventory, resource utilization, throughput, and number of tardy jobs were separately employed as the fitness functions in solving these three problems. The results for all three problems showed that real-valued code GAs can clearly represent the corresponding solution set of the problem and accurately find the optimal solutions in a shorter searching time. The genetic algorithm approach for the XOR problem, the inverse kinematics problem for robots with multiple degrees of freedom, and the job shop scheduling problem is proving to be a promising direction for finding near-optimal solutions to engineering optimization problems.
Rabello Luis (Advisor)
164 p.
Engineering, Industrial
Integration; Genetic algorithms; Engineering optimization problems

Recommended Citations

Citations

  • Tsai, J.-S. (1993). Integration of genetic algorithms to engineering optimization problems [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1176310901

    APA Style (7th edition)

  • Tsai, Jay-Shinn. Integration of genetic algorithms to engineering optimization problems. 1993. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1176310901.

    MLA Style (8th edition)

  • Tsai, Jay-Shinn. "Integration of genetic algorithms to engineering optimization problems." Master's thesis, Ohio University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1176310901

    Chicago Manual of Style (17th edition)

ohiou1176310901
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© 1993, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.