Multi-project scheduling problem under shared multi-skill resource constraints

Haroune, Meya; Dhib, Cheikh; Néron, Emmanuel; Soukhal, Ameur; Babou, Hafed Mohamed; Nanne, Mohamedade Farouk

doi:10.1007/s11750-022-00633-5

Cited by 9 publications

(4 citation statements)

References 55 publications

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“…Cui et al [6] developed a variable neighborhood search algorithm to solve multi-model multiskilled multi-project scheduling problems. Haroune et al [49] proposed a local search and a tabu search algorithm to tackle the multi-project scheduling and multi-skilled employees assignment problem with hard and soft constraints. Some studies (Chen et al [50]; Hosseinian and Baradaran [51]) have proposed different approaches for solving the multiskilled multi-project scheduling problem.…”

Section: B Multi-skilled Project Scheduling Problemmentioning

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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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: B Multi-skilled Project Scheduling Problemmentioning

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 [20], a mixed-integer goal programming model and a three-phase greedy heuristic method are introduced for the multi-project scheduling and multi-skilled employee assignment problem. The method addresses constraints like mini-mum task load and limits on tasks per week per employee, employing a local and tabu search algorithm.…”

Section: Related Workmentioning

confidence: 99%

Weighted Multi-Skill Resource Constrained Project Scheduling: A Greedy and Parallel Scheduling Approach

Akbar,

Zubair,

Khan

et al. 2024

IEEE Access

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This study addresses the Weighted Multi-Skill Resource Constrained Project Scheduling Problem (W-MSRCSPSP) with the aim of minimizing software project makespan. Unlike previous works, our investigation regards heterogeneous resources characterized by varying skill proficiency levels. Another major problem with existing methodologies is the potential underutilization of human resources due to varying task durations. This work introduces an innovative scheduling approach known as the Greedy and Parallel Scheduling (GPS) algorithm to handle the said issues. GPS focuses on assigning the most suitable resources available to project activities at each scheduling point. The fundamental goal of our proposed approach is to reduce resource wastage while efficiently allocating surplus resources, if any, to project tasks, ultimately leading to a decrease in the makespan. To empirically evaluate the efficacy of the GPS algorithm, we conduct a comparative analysis against the Parallel Scheduling Scheme (PSS). The advantage of our proposed approach lies in its ability to optimize the utilization of available resources, resulting in accelerated project completion. Results from extensive simulations substantiate this claim, demonstrating that the GPS scheme outperforms the PSS approach in minimizing project duration.

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“…As stated by Demeulemeester and Herroelen, this leads to another management challenge, namely deciding the resource allocation from one resource pool across different parallel projects. This area of resource management is referred to as project scheduling and a variety of project scheduling problems are subject to past and current research (Neumann, 2003;Haroune et al, 2021) The project scheduling problem most relevant to the approach presented in this paper is called "Resource Constraint Project Scheduling Problem" (RCPSP). It describes the problem of having limited resources for multiple projects while each projects duration is subject to minimization (Cavalcante et al, 2013;Artigues, 2010).…”

Section: Project Schedulingmentioning

confidence: 99%

“…The authors associate the human resource with different competencies and also incorporate the idea of learning behaviour of the resources. The approach discussed by Haroune et al (2021) presents a multi-project and multi-skill concept for resolving the RCPSP. The goal is to derive schedules for project managers in a setting of various projects per manager and a shared and limited resource pool of teams with limited capacities and various skills.…”

Section: Current Research In Project Schedulingmentioning

confidence: 99%

Framework for FAMD-Based Identification of RCPSP-Constraints for Improved Project Scheduling

et al. 2022

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Product development in today's manufacturing companies is characterized by multiple development projects under intense time constraints. This means that the success of projects impacts the company's success significantly. However, industrial practices show that many projects fail to meet their time targets. This paper presents a methodology to systematically improve project schedule adherence of development projects by combining exploratory data analysis of historic project data with project scheduling optimizations to enhance the project schedules and enable more successful projects.

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Multi-project scheduling problem under shared multi-skill resource constraints

Cited by 9 publications

References 55 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

Weighted Multi-Skill Resource Constrained Project Scheduling: A Greedy and Parallel Scheduling Approach

Framework for FAMD-Based Identification of RCPSP-Constraints for Improved Project Scheduling

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