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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9298873/ |
| _version_ | 1819275691849416704 |
|---|---|
| author | Dongning Liu Zhe Xu |
| author_facet | Dongning Liu Zhe Xu |
| author_sort | Dongning Liu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-23T23:28:21Z |
| format | Article |
| id | doaj.art-0d39fefeba1e4dfe9e34439328c82cdd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:28:21Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-0d39fefeba1e4dfe9e34439328c82cdd2022-12-21T17:26:09ZengIEEEIEEE 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 |
| 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 |
| title | 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_short | 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 |
| topic | Heuristic algorithms multi-project scheduling priority rule uncertainty |
| url | https://ieeexplore.ieee.org/document/9298873/ |
| work_keys_str_mv | AT dongningliu amultiprheuristicfordistributedmultiprojectschedulingwithuncertainduration AT zhexu amultiprheuristicfordistributedmultiprojectschedulingwithuncertainduration AT dongningliu multiprheuristicfordistributedmultiprojectschedulingwithuncertainduration AT zhexu multiprheuristicfordistributedmultiprojectschedulingwithuncertainduration |