Using genetic algorithms to facilitate schedule optimization
Date of Publication
2000
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Civil Engineering
Subject Categories
Civil Engineering
College
Gokongwei College of Engineering
Department/Unit
Civil Engineering
Honor/Award
Awarded as best thesis, 2000
Abstract/Summary
Abstract. The common approach used in solving a principal subset of the time-cost trade-off problems in project management is through network compression. Network compression is an essential tool for the effective and efficient implementation of a project. However, for large projects with thousands of activities as is normal for most private commercial and industrial projects and major government infrastructure projects, this approach becomes unfeasible, whether done manually, with or without the aid of the available commercial project management software, or through currently available computational approaches. This paper uses genetic algorithms (GAs), a set of tools based on natural selection and the mechanisms of population genetics, to solve the problem of network compression. A different perspective on the problem from that used in network compression, however, is taken and the problem is termed as schedule optimization. The approach presented in this paper allowed a powerful and user-friendly program to be developed for solving the problem of schedule optimization that is suitable for practical and commercial purposes.
Abstract Format
html
Language
English
Format
Accession Number
TU09897
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
120 leaves
Recommended Citation
Que, B., Barrientos, R., & Cheng, J. (2000). Using genetic algorithms to facilitate schedule optimization. Retrieved from https://animorepository.dlsu.edu.ph/etd_honors/138
