A genetic local search approach to the bid evaluation problem in an automated contracting environment
Date of Publication
2002
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
Subject Categories
Databases and Information Systems
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Remedios Bulos
Defense Panel Chair
Lindsley Abadia
Defense Panel Member
Charibeth Ko Cheng
Caslon Chua
Abstract/Summary
In automated contracting, bid evaluation is a difficult task because finding the optimal set of bids which can be composed into a feasible plan requires taking into account time constraints and risk estimates in addition to price. A simulated annealing-based approach has been implemented to deal with evaluating bids of complex plans. This research offers an alternative approach to the bid evaluation problem based on the genetic local search (GLS) method. GLS has been shown to be very effective for several combinatorial optimization problems and for some cases proved to be superior to other search approaches including simulated annealing.
Abstract Format
html
Language
English
Format
Accession Number
TG03314
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
vi, 74 leaves; 28 cm.
Keywords
Genetic algorithms; Combinatorial optimization; Contracts; Letting of; Construction industry-- Automation
Recommended Citation
Alvarez, M. R. (2002). A genetic local search approach to the bid evaluation problem in an automated contracting environment. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/2920