CEC Theses and Dissertations

Title

Planning Genetic Algorithm: Pursuing Meta-knowledge

Date of Award

1999

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Graduate School of Computer and Information Sciences

Advisor

Raul Salazar

Committee Member

Maxine S. Cohen

Committee Member

S. Rollins Guild

Abstract

This study focuses on improving business planning by proposing a series of artificial intelligence techniques to facilitate the integration of decision support systems and expert system paradigms. The continued evolution of the national information infrastructure, open systems interconnectivity, and electronic data interchange lends toward the future plausibility of the inclusion of a back-end genetic algorithm approach. By using a back-end genetic algorithm, meta-planning knowledge could be collected, extended to external data sources, and utilized to improve business decision making.

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