A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration

Multiple projects are often managed and run in a decentralized setting. In this paper, considering the uncertainty in project implementation, we study the distributed multi-project scheduling problem with uncertain duration. A multi-PR heuristic (MPR-H) is then proposed to dynamically coordinate the...

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Main Authors: Dongning Liu, Zhe Xu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9298873/
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spelling doaj-0d39fefeba1e4dfe9e34439328c82cdd2021-03-30T04:18:47ZengIEEEIEEE Access2169-35362020-01-01822778022779210.1109/ACCESS.2020.30457139298873A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain DurationDongning Liu0Zhe Xu1https://orcid.org/0000-0002-7342-6964College of Economics and Management, Beihang University, Beijing, ChinaCollege of Economics and Management, Beihang University, Beijing, ChinaMultiple projects are often managed and run in a decentralized setting. In this paper, considering the uncertainty in project implementation, we study the distributed multi-project scheduling problem with uncertain duration. A multi-PR heuristic (MPR-H) is then proposed to dynamically coordinate the global resource conflicts while minimizing the expected total tardiness cost. Three priority rules based on current known information are also proposed and incorporated in our approach. We further consider the opportunistic behaviour of self-interested agents and design a payment negotiation process which is added to the MPR-H. In this paper, we then evaluate the performance of the MPR-H on the benchmark dataset MPSPLIB. The computational results confirm that MPR-H achieves significant improvements in comparison with several state-of-the-art distributed/centralized algorithms. The proposed algorithm also provides the senior manager with an efficient method to allocate global resources for large-size and strong conflicting instances under various activity duration distributions. Besides, we show that multi-projects with relative slack global resource constraints are more affected by the change of uncertainty. By analyzing the strategic behaviour of the agents in problems with two projects, we also show that in our MPR-H with payment negotiation approach, rational agents have to behave truthfully that is the dominant-strategy equilibrium leading to high-quality results.https://ieeexplore.ieee.org/document/9298873/Heuristic algorithmsmulti-project schedulingpriority ruleuncertainty
collection DOAJ
language English
format Article
sources DOAJ
author Dongning Liu
Zhe Xu
spellingShingle Dongning Liu
Zhe Xu
A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
IEEE Access
Heuristic algorithms
multi-project scheduling
priority rule
uncertainty
author_facet Dongning Liu
Zhe Xu
author_sort Dongning Liu
title A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
title_short A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
title_full A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
title_fullStr A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
title_full_unstemmed A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration
title_sort multi-pr heuristic for distributed multi-project scheduling with uncertain duration
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Multiple projects are often managed and run in a decentralized setting. In this paper, considering the uncertainty in project implementation, we study the distributed multi-project scheduling problem with uncertain duration. A multi-PR heuristic (MPR-H) is then proposed to dynamically coordinate the global resource conflicts while minimizing the expected total tardiness cost. Three priority rules based on current known information are also proposed and incorporated in our approach. We further consider the opportunistic behaviour of self-interested agents and design a payment negotiation process which is added to the MPR-H. In this paper, we then evaluate the performance of the MPR-H on the benchmark dataset MPSPLIB. The computational results confirm that MPR-H achieves significant improvements in comparison with several state-of-the-art distributed/centralized algorithms. The proposed algorithm also provides the senior manager with an efficient method to allocate global resources for large-size and strong conflicting instances under various activity duration distributions. Besides, we show that multi-projects with relative slack global resource constraints are more affected by the change of uncertainty. By analyzing the strategic behaviour of the agents in problems with two projects, we also show that in our MPR-H with payment negotiation approach, rational agents have to behave truthfully that is the dominant-strategy equilibrium leading to high-quality results.
topic Heuristic algorithms
multi-project scheduling
priority rule
uncertainty
url https://ieeexplore.ieee.org/document/9298873/
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