Exact algorithms for the 0–1 Time-Bomb Knapsack Problem

We consider a stochastic version of the 0–1 Knapsack Problem in which, in addition to profit and weight, each item is associated with a probability of exploding and destroying all the contents of the knapsack. The objective is to maximise the expected profit of the selected items. The resulting prob...

Descripción completa

Detalles Bibliográficos
Autores: Monaci, Michele, Pike-Burke, Ciara, Santini, Alberto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/57585
Acceso en línea:http://hdl.handle.net/10230/57585
http://dx.doi.org/10.1016/j.cor.2022.105848
Access Level:acceso abierto
Palabra clave:Knapsack Problem
Stochastic optimisation
Exact algorithms
Computational experiments
id ES_f945c82742623addfbc2d90ebb0c33fa
oai_identifier_str oai:recercat.cat:10230/57585
network_acronym_str ES
network_name_str España
repository_id_str
spelling Exact algorithms for the 0–1 Time-Bomb Knapsack ProblemMonaci, MichelePike-Burke, CiaraSantini, AlbertoKnapsack ProblemStochastic optimisationExact algorithmsComputational experimentsWe consider a stochastic version of the 0–1 Knapsack Problem in which, in addition to profit and weight, each item is associated with a probability of exploding and destroying all the contents of the knapsack. The objective is to maximise the expected profit of the selected items. The resulting problem, denoted as 0–1 Time-Bomb Knapsack Problem (01-TB-KP), has applications in logistics and cloud computing scheduling. We introduce a nonlinear mathematical formulation of the problem, study its computational complexity, and propose techniques to derive upper and lower bounds using convex optimisation and integer linear programming. We present three exact approaches based on enumeration, branch and bound, and dynamic programming, and computationally evaluate their performance on a large set of benchmark instances. The computational analysis shows that the proposed methods outperform the direct application of nonlinear solvers on the mathematical model, and provide high quality solutions in a limited amount of time.Elsevier202320232022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/57585http://dx.doi.org/10.1016/j.cor.2022.105848reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésComputers and Operations Research. 2022;145:105848.© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/575852026-05-29T05:05:01Z
dc.title.none.fl_str_mv Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
title Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
spellingShingle Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
Monaci, Michele
Knapsack Problem
Stochastic optimisation
Exact algorithms
Computational experiments
title_short Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
title_full Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
title_fullStr Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
title_full_unstemmed Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
title_sort Exact algorithms for the 0–1 Time-Bomb Knapsack Problem
dc.creator.none.fl_str_mv Monaci, Michele
Pike-Burke, Ciara
Santini, Alberto
author Monaci, Michele
author_facet Monaci, Michele
Pike-Burke, Ciara
Santini, Alberto
author_role author
author2 Pike-Burke, Ciara
Santini, Alberto
author2_role author
author
dc.subject.none.fl_str_mv Knapsack Problem
Stochastic optimisation
Exact algorithms
Computational experiments
topic Knapsack Problem
Stochastic optimisation
Exact algorithms
Computational experiments
description We consider a stochastic version of the 0–1 Knapsack Problem in which, in addition to profit and weight, each item is associated with a probability of exploding and destroying all the contents of the knapsack. The objective is to maximise the expected profit of the selected items. The resulting problem, denoted as 0–1 Time-Bomb Knapsack Problem (01-TB-KP), has applications in logistics and cloud computing scheduling. We introduce a nonlinear mathematical formulation of the problem, study its computational complexity, and propose techniques to derive upper and lower bounds using convex optimisation and integer linear programming. We present three exact approaches based on enumeration, branch and bound, and dynamic programming, and computationally evaluate their performance on a large set of benchmark instances. The computational analysis shows that the proposed methods outperform the direct application of nonlinear solvers on the mathematical model, and provide high quality solutions in a limited amount of time.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/57585
http://dx.doi.org/10.1016/j.cor.2022.105848
url http://hdl.handle.net/10230/57585
http://dx.doi.org/10.1016/j.cor.2022.105848
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Computers and Operations Research. 2022;145:105848.
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869425079289380864
score 15.811543

Similares en LA Referencia