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

Print

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

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