An iterative auction for resource-constrained surgical scheduling

Liu, Lu; Wang, Chun; Wang, Jianjun; Crespo, António

doi:10.1080/01605682.2022.2083988

Cited by 5 publications

(4 citation statements)

References 37 publications

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“…The local decision-makers submitted a bid consisting of the resource requirement of the eligible activity and the bid price, and the global decision-maker determined the winner of each auction round via a heuristic procedure. Liu et al [18] proposed a combinatorial auction mechanism to solve the decentralized surgical scheduling problem with conflicting multiple renewable resource requirements. Other researchers (Song et al [13]; Arauzo et al [19]) have also used the auction-based mechanisms to deal with the DR-CMPSP.…”

Section: A Decentralized Multi-project Scheduling Problemmentioning

confidence: 99%

“…The formula (17) determines the updated pulse rate h c+1 k of bat B k , where h max represents the maximum value of the pulse rate, exp represents the exponential function operations, and c represents the number of iterations. The formula (18) calculates the updated ultrasonic loudness A c+1 k of bat B k , where A c k denotes the ultrasonic loudness of bat B k at the cth iteration. χ and β are the adaptation parameters, which are set to χ = β = 0.9 [53].…”

Section: ) Position Updatementioning

confidence: 99%

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A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

You,

Xu,

Zhao

2024

IEEE Access

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With the rapid development of economic globalization and information technology, the projects undertaken by enterprises are gradually becoming larger and more complex. The multi-project management model has become the norm in enterprise management, and it shows a trend of decentralization in terms of geographical distribution and management environment. This decentralization mainly manifests in the fact that each project has its own private information and benefit objectives and shares limited global resources with other projects during the execution process, forming a decentralized decision-making environment. As an extension of the resource-constrained project scheduling problem (RCPSP), the decentralized resourceconstrained multi-project scheduling problem (DRCMPSP) is a project scheduling problem that integrates single project scheduling and global resource coordination allocation in a decentralized decision-making environment with multiple independent decision-makers. Furthermore, when considering global resources as multi-skilled staff, the decentralized resource-constrained multi-project scheduling problem sharing multi-skilled staff (DRCMPSP-MS) studied in this paper is proposed. A two-layer model containing local scheduling and global coordination decision-making is established to describe this problem. To solve this problem, a two-layer approach (TLA) is proposed. In the local scheduling layer, a bat algorithm based on forward-backward scheduling (BAFBS) is developed to generate local baseline schedules to minimize the single-project completion time. In the global coordination decision-making layer, a variable neighborhood tabu search algorithm with greedy assignment strategy (VNTS-GAS) is designed to resolve global resource conflicts to minimize the multi-project total tardiness cost. Computational experiments are conducted based on the Multi-Project Scheduling Problem LIBrary (MPSPLIB) dataset. The results show that the BAFBS can obtain high-quality local baseline schedules. Compared to the existing decentralized and centralized methods, our proposed TLA can obtain better solutions on most problem subsets, which proves that our approach can effectively coordinate the allocation of multi-skilled staff among multiple projects.INDEX TERMS Decentralized multi-project scheduling, multi-skilled staff, two-layer approach, tabu search, bat algorithmThis article has been accepted for publication in IEEE Access.

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Section: A Decentralized Multi-project Scheduling Problemmentioning

confidence: 99%

Section: ) Position Updatementioning

confidence: 99%

A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

You,

Xu,

Zhao

2024

IEEE Access

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“…In their auction procedure, each bid was evaluated by the capacity query process, and the winner determination problem was solved via a greedy strategy and a branch-and-bound approach. Liu et al (2023a) proposed a combinatorial auction mechanism to solve the decentralized surgical scheduling problem with conflicting multiple renewable resource requirements. The mechanism was comprised of three components: requirement-based bid, winner determination model, and iterative bidding procedure.…”

Section: Decentralized Multiproject Scheduling Problemmentioning

confidence: 99%

“…Liu et al. (2023a) proposed a combinatorial auction mechanism to solve the decentralized surgical scheduling problem with conflicting multiple renewable resource requirements. The mechanism was comprised of three components: requirement‐based bid, winner determination model, and iterative bidding procedure.…”

Section: Literature Reviewmentioning

confidence: 99%

A two‐layer approach for solving robust decentralized multiproject scheduling problem with multi‐skilled staff

You,

Xu,

et al. 2023

Int Trans Operational Res

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Uncertain activity durations and multi‐skilled staff allocation are two practical factors that are difficult to cope with in real project management. This paper studies a new decentralized resource‐constrained multiproject scheduling problem with uncertain activity durations and multi‐skilled staff allocation. The robust project scheduling is employed to tackle uncertainty. We name it the robust decentralized resource‐constrained multiproject scheduling problem with multi‐skilled staff (RDMPSP‐MS). To formulate this problem, a two‐layer model containing local scheduling and global coordination decision‐making is established based on the multiagent system. To solve this model, a two‐layer approach (TLA) is developed. In the TLA, a starting time criticality heuristic method is adopted to handle the local scheduling problem, and a global resource allocation heuristic algorithm is designed to allocate multi‐skilled staff. The computational experiments are conducted on the adapted Multi‐Project Scheduling Problem LIBrary (MPSPLIB) data set. The results show that the proposed TLA outperforms seven heuristic algorithms based on priority rules regarding solution quality and efficiency on most problem subsets. It is further verified that the robustness of the baseline schedule deteriorates with the increase in problem size and activity duration variability level. Additionally, the results of this research provide practical guidance for managers who expect to determine reasonable project deadlines in a decentralized multiproject environment.

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A performance-impact based multi-task distributed scheduling algorithm with task removal inference and deadlock avoidance

Li,

Chen,

Wang

et al. 2023

Auton Agent Multi-Agent Syst

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An iterative auction for resource-constrained surgical scheduling

Cited by 5 publications

References 37 publications

A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

A two‐layer approach for solving robust decentralized multiproject scheduling problem with multi‐skilled staff

A performance-impact based multi-task distributed scheduling algorithm with task removal inference and deadlock avoidance

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