A genetic local search approach to the bid evaluation problem in an automated contracting environment

A genetic local search approach to the bid evaluation problem in an automated contracting environment

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 wit...

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Main Author: Alvarez, Maria Fe R.
Format: text
Language:English
Published: Animo Repository 2002
Subjects:
Genetic algorithms
Combinatorial optimization
Contracts
Letting of
Construction industry > Automation
Databases and Information Systems
Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/2920
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_masteral-9758
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_masteral-97582022-07-20T06:33:47Z A genetic local search approach to the bid evaluation problem in an automated contracting environment Alvarez, Maria Fe R. 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. 2002-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_masteral/2920 Master's Theses English Animo Repository Genetic algorithms Combinatorial optimization Contracts Letting of Construction industry-- Automation Databases and Information Systems
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Genetic algorithms
Combinatorial optimization
Contracts
Letting of
Construction industry-- Automation
Databases and Information Systems
spellingShingle Genetic algorithms
Combinatorial optimization
Contracts
Letting of
Construction industry-- Automation
Databases and Information Systems
Alvarez, Maria Fe R.
A genetic local search approach to the bid evaluation problem in an automated contracting environment
description 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.
format text
author Alvarez, Maria Fe R.
author_facet Alvarez, Maria Fe R.
author_sort Alvarez, Maria Fe R.
title A genetic local search approach to the bid evaluation problem in an automated contracting environment
title_short A genetic local search approach to the bid evaluation problem in an automated contracting environment
title_full A genetic local search approach to the bid evaluation problem in an automated contracting environment
title_fullStr A genetic local search approach to the bid evaluation problem in an automated contracting environment
title_full_unstemmed A genetic local search approach to the bid evaluation problem in an automated contracting environment
title_sort genetic local search approach to the bid evaluation problem in an automated contracting environment
publisher Animo Repository
publishDate 2002
url https://animorepository.dlsu.edu.ph/etd_masteral/2920
_version_ 1738854827711004672

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