Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A nature inspired metaheuristic for optimal leveling of resources in project management
Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Chios, Greece.ORCID iD: 0000-0002-1319-513X
Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Chios, Greece.
Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Chios, Greece.
Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, Chios, Greece.
Show others and affiliations
2018 (English)In: SETN '18: Proceedings of the 10th Hellenic Conference on Artificial Intelligence, ACM Digital Library, 2018, article id 17Conference paper, Published paper (Refereed)
Abstract [en]

Resource Leveling is a constrained problem with a large solution space, especially when the projects have numerous tasks. This makes the problem hard to tackle. In this study, a novel algorithm named sonar inspired optimization (SIO) belonging in Nature Inspired Intelligence is applied in both benchmark and artificial resource-leveling problems to investigate its performance. Results are compared to those derived from a Hybrid Genetic Algorithm (HGA) previously developed. Experimental findings show that the proposed algorithm is very promising as in most cases the obtained solutions prove superior or equally good to those of HGA and other competitive approaches. An additional approach of the proposed metaheuristic is that it generates only feasible solutions. The algorithm has been implemented in different programming languages so that in future applications will be user friendly for project managers.

Place, publisher, year, edition, pages
ACM Digital Library, 2018. article id 17
Series
ACM International Conference Proceeding Series
Keywords [en]
Nature-inspired algorithms, Resource Leveling, Sonar Inspired Optimization, Artificial intelligence, Benchmarking, Constraint theory, Genetic algorithms, Problem oriented languages, Sonar, Constrained problem, Feasible solution, Future applications, Hybrid genetic algorithms, Large solutions, Nature inspired algorithms, Project managers, Project management
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-63838DOI: 10.1145/3200947.3201014Scopus ID: 2-s2.0-85052014752ISBN: 9781450364331 (print)OAI: oai:DiVA.org:hj-63838DiVA, id: diva2:1845903
Conference
10th Hellenic Conference on Artificial Intelligence, SETN 2018, 9-12 July 2018
Available from: 2024-03-20 Created: 2024-03-20 Last updated: 2024-03-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Tzanetos, Alexandros

Search in DiVA

By author/editor
Tzanetos, Alexandros
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 18 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf