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An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project

In a collaborative product design project, reasonable resource allocation can shorten the development cycle and reduce cost. Team capacity evaluation and a task-team scheduling model are presented. A collaborative team capacity model is constructed, and a 2-tuple linguistic method is used to evaluat...

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Detalles Bibliográficos
Autores principales: Wang, Xiaolei, Ci, Tiejun, Tsai, Sang-Bing, Liu, Aijun, Chen, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070215/
https://www.ncbi.nlm.nih.gov/pubmed/30067816
http://dx.doi.org/10.1371/journal.pone.0200753
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author Wang, Xiaolei
Ci, Tiejun
Tsai, Sang-Bing
Liu, Aijun
Chen, Quan
author_facet Wang, Xiaolei
Ci, Tiejun
Tsai, Sang-Bing
Liu, Aijun
Chen, Quan
author_sort Wang, Xiaolei
collection PubMed
description In a collaborative product design project, reasonable resource allocation can shorten the development cycle and reduce cost. Team capacity evaluation and a task-team scheduling model are presented. A collaborative team capacity model is constructed, and a 2-tuple linguistic method is used to evaluate the capacity of collaborative teams. Next, the matching degree between design task and collaborative team is defined. A collaborative product design scheduling model considering task-team matching is developed. Combined with the simulated annealing operator, based on the single-coding strategy, self-adaptive multi-point cross and mutation, an improved genetic algorithm is proposed to solve the model. Finally, a case study is presented to validate the method.
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spelling pubmed-60702152018-08-09 An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project Wang, Xiaolei Ci, Tiejun Tsai, Sang-Bing Liu, Aijun Chen, Quan PLoS One Research Article In a collaborative product design project, reasonable resource allocation can shorten the development cycle and reduce cost. Team capacity evaluation and a task-team scheduling model are presented. A collaborative team capacity model is constructed, and a 2-tuple linguistic method is used to evaluate the capacity of collaborative teams. Next, the matching degree between design task and collaborative team is defined. A collaborative product design scheduling model considering task-team matching is developed. Combined with the simulated annealing operator, based on the single-coding strategy, self-adaptive multi-point cross and mutation, an improved genetic algorithm is proposed to solve the model. Finally, a case study is presented to validate the method. Public Library of Science 2018-08-01 /pmc/articles/PMC6070215/ /pubmed/30067816 http://dx.doi.org/10.1371/journal.pone.0200753 Text en © 2018 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Xiaolei
Ci, Tiejun
Tsai, Sang-Bing
Liu, Aijun
Chen, Quan
An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title_full An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title_fullStr An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title_full_unstemmed An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title_short An empirical study of collaborative capacity evaluation and scheduling optimization for a CPD project
title_sort empirical study of collaborative capacity evaluation and scheduling optimization for a cpd project
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070215/
https://www.ncbi.nlm.nih.gov/pubmed/30067816
http://dx.doi.org/10.1371/journal.pone.0200753
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