Competitive algorithms for online conversion problems with interrelated prices

The classical uni-directional conversion algorithms are based on the assumption that prices are arbitrarily chosen from the fixed price interval[m, M] where m and M represent the estimated lower and upper bounds of possible prices 0<m<M. The estimated interval is erroneous and no attempts are...

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Main Authors:	Iqbal, Javeria, Ahmad, Iftikhar, Shah, Asadullah
Format:	Article
Language:	English English
Published:	The Science and Information (SAI) Organization Limited 2019
Subjects:	T10.5 Communication of technical information
Online Access:	http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/7/74100%20Competitive%20Algorithms%20for%20Online%20Conversion.pdf http://irep.iium.edu.my/74100/8/74100%20Competitive%20Algorithms%20for%20Online%20Conversion%20SCOPUS.pdf

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recordtype	eprints
spelling	iium-741002019-09-13T02:16:00Z http://irep.iium.edu.my/74100/ Competitive algorithms for online conversion problems with interrelated prices Iqbal, Javeria Ahmad, Iftikhar Shah, Asadullah T10.5 Communication of technical information The classical uni-directional conversion algorithms are based on the assumption that prices are arbitrarily chosen from the fixed price interval[m, M] where m and M represent the estimated lower and upper bounds of possible prices 0<m<M. The estimated interval is erroneous and no attempts are made by the algorithms to update the erroneous estimates. We consider a real world setting where prices are interrelated, i.e., each price depends on its preceding price. Under this assumption, we drive a lower bound on the competitive ratio of randomized non-primitive algorithms. Motivated by the fixed and erroneous price bounds, we present an update model that progressively improves the bounds. Based on the update model, we propose a non-preemptive reservations price algorithm RP* and analyze it under competitive analysis. Finally, we report the findings of an experimental study that is conducted over the real world stock index data. We observe that RP* consistently outperforms the classical algorithm. The Science and Information (SAI) Organization Limited 2019 Article PeerReviewed application/pdf en http://irep.iium.edu.my/74100/7/74100%20Competitive%20Algorithms%20for%20Online%20Conversion.pdf application/pdf en http://irep.iium.edu.my/74100/8/74100%20Competitive%20Algorithms%20for%20Online%20Conversion%20SCOPUS.pdf Iqbal, Javeria and Ahmad, Iftikhar and Shah, Asadullah (2019) Competitive algorithms for online conversion problems with interrelated prices. International Journal of Advanced Computer Science and Applications (IJACSA), 10 (6). pp. 582-589. ISSN 2158-107X E-ISSN 2156-5570 https://thesai.org/Downloads/Volume10No6/Paper_75-Competitive_Algorithms_for_Online_Conversion_Problem.pdf 10.14569/IJACSA.2019.0100675
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T10.5 Communication of technical information
spellingShingle	T10.5 Communication of technical information Iqbal, Javeria Ahmad, Iftikhar Shah, Asadullah Competitive algorithms for online conversion problems with interrelated prices
description	The classical uni-directional conversion algorithms are based on the assumption that prices are arbitrarily chosen from the fixed price interval[m, M] where m and M represent the estimated lower and upper bounds of possible prices 0<m<M. The estimated interval is erroneous and no attempts are made by the algorithms to update the erroneous estimates. We consider a real world setting where prices are interrelated, i.e., each price depends on its preceding price. Under this assumption, we drive a lower bound on the competitive ratio of randomized non-primitive algorithms. Motivated by the fixed and erroneous price bounds, we present an update model that progressively improves the bounds. Based on the update model, we propose a non-preemptive reservations price algorithm RP* and analyze it under competitive analysis. Finally, we report the findings of an experimental study that is conducted over the real world stock index data. We observe that RP* consistently outperforms the classical algorithm.
format	Article
author	Iqbal, Javeria Ahmad, Iftikhar Shah, Asadullah
author_facet	Iqbal, Javeria Ahmad, Iftikhar Shah, Asadullah
author_sort	Iqbal, Javeria
title	Competitive algorithms for online conversion problems with interrelated prices
title_short	Competitive algorithms for online conversion problems with interrelated prices
title_full	Competitive algorithms for online conversion problems with interrelated prices
title_fullStr	Competitive algorithms for online conversion problems with interrelated prices
title_full_unstemmed	Competitive algorithms for online conversion problems with interrelated prices
title_sort	competitive algorithms for online conversion problems with interrelated prices
publisher	The Science and Information (SAI) Organization Limited
publishDate	2019
url	http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/ http://irep.iium.edu.my/74100/7/74100%20Competitive%20Algorithms%20for%20Online%20Conversion.pdf http://irep.iium.edu.my/74100/8/74100%20Competitive%20Algorithms%20for%20Online%20Conversion%20SCOPUS.pdf
first_indexed	2023-09-18T21:44:59Z
last_indexed	2023-09-18T21:44:59Z
_version_	1777413389581025280

Competitive algorithms for online conversion problems with interrelated prices

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