A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes
In the highly dynamic design environments, task allocation is subject to considerable design changes. The task reallocating to cope with various unexpected design changes becomes an increasingly important issue in the complex product design (CPD). In this paper, we propose a task reallocating model...
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doaj-c08395d293e44d13b1ee6e8e2316306a2021-03-30T00:58:46ZengIEEEIEEE Access2169-35362019-01-01716822616823510.1109/ACCESS.2019.29542048906093A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design ChangesYinhe Wang0Meng Wei1https://orcid.org/0000-0002-0743-7745Jiafu Su2https://orcid.org/0000-0002-6001-5744Hongyuan Hu3Heng Wang4College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, ChinaCollege of Mechanical Engineering, Chongqing University, Chongqing, ChinaChongqing Key Laboratory of Electronic Commerce and Supply Chain System, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, ChinaSchool of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, ChinaCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, ChinaIn the highly dynamic design environments, task allocation is subject to considerable design changes. The task reallocating to cope with various unexpected design changes becomes an increasingly important issue in the complex product design (CPD). In this paper, we propose a task reallocating model based on an adaptive multi-objective genetic algorithm and Tabu search (AMOGATS) method to study the dynamic task allocating procedure considering design changes, which integrates the advantages of adaptive genetic algorithm and Tabu search algorithm. Three objectives, i.e. completion time, robustness and stability, are considered simultaneously to measure the task allocation performance. A real example is employed to test and evaluate the performance of proposed method. The computational results imply that the proposed AMOGATS performs better than the heuristic algorithms available in the literature, which has more advantages on the convergence rate and running efficiency than the other algorithms, along with a better solution. This work provides a useful decision support to carry out the task reallocating with high levels of flexibility and efficiency during the process of CPD.https://ieeexplore.ieee.org/document/8906093/Task reallocatinghybrid-drivenrobustness and stabilitydesign changeAMOGATS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yinhe Wang Meng Wei Jiafu Su Hongyuan Hu Heng Wang |
spellingShingle |
Yinhe Wang Meng Wei Jiafu Su Hongyuan Hu Heng Wang A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes IEEE Access Task reallocating hybrid-driven robustness and stability design change AMOGATS |
author_facet |
Yinhe Wang Meng Wei Jiafu Su Hongyuan Hu Heng Wang |
author_sort |
Yinhe Wang |
title |
A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes |
title_short |
A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes |
title_full |
A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes |
title_fullStr |
A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes |
title_full_unstemmed |
A Multi-Objective Task Reallocating Method in Complex Product Design Process Considering Design Changes |
title_sort |
multi-objective task reallocating method in complex product design process considering design changes |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
In the highly dynamic design environments, task allocation is subject to considerable design changes. The task reallocating to cope with various unexpected design changes becomes an increasingly important issue in the complex product design (CPD). In this paper, we propose a task reallocating model based on an adaptive multi-objective genetic algorithm and Tabu search (AMOGATS) method to study the dynamic task allocating procedure considering design changes, which integrates the advantages of adaptive genetic algorithm and Tabu search algorithm. Three objectives, i.e. completion time, robustness and stability, are considered simultaneously to measure the task allocation performance. A real example is employed to test and evaluate the performance of proposed method. The computational results imply that the proposed AMOGATS performs better than the heuristic algorithms available in the literature, which has more advantages on the convergence rate and running efficiency than the other algorithms, along with a better solution. This work provides a useful decision support to carry out the task reallocating with high levels of flexibility and efficiency during the process of CPD. |
topic |
Task reallocating hybrid-driven robustness and stability design change AMOGATS |
url |
https://ieeexplore.ieee.org/document/8906093/ |
work_keys_str_mv |
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