Solving the resource-constrained multi-project scheduling problem with an improved critical chain method

Tian, Min; Liu, Ren Jing; Zhang, Guangjun

doi:10.1080/01605682.2019.1609883

Cited by 15 publications

(8 citation statements)

References 26 publications

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“…Constraint (3) represents the local resource constraint to ensure that at any time point t, the local resource r required by all activities does not exceed the available capacity of resource r. Constraint (4) ensures that the finish-to-start precedence relationships are fulfilled, i.e., any activity cannot start until all its predecessor activities have been completed. Constraint (5) indicates that the start time of project i cannot be earlier than its release time ad i , where x i0t equals 1 if dummy start activity a i0 ends at time t, and equals 0 otherwise. Constraint (6) denotes the decision variable.…”

Section: ) Local Scheduling Modelmentioning

confidence: 99%

“…The multi-project operation mode has become the primary way for many enterprises to manage complex tasks efficiently. As an extension of the RCPSP, the resource-constrained multi-project scheduling problem (RCMPSP) has been widely studied in recent years [5]- [8]. The RCMPSP not only needs to satisfy the priority relationship constraints and local resource constraints, but also involves the reasonable allocation of global resources among projects when scheduling multi-project activities.…”

Section: Introductionmentioning

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: ) Local Scheduling Modelmentioning

confidence: 99%

Section: Introductionmentioning

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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“…Zoraghi et al [36] studied the combination of a multimode project scheduling problem and material ordering, and used multiobjective evolutionary algorithms, including intensity Pareto evolution II, multiobjective particle swarm optimization and multiobjective evolution based on decomposition, to solve the developed three-objective problem. Tian et al [37] proposed an improved critical chain technology for solving resource-constrained multiproject scheduling by studying the resource flow characteristics of single project, multiproject and activity. GAs are based on biological evolution compared with the other algorithms.…”

Section: Resource-constrained Project Scheduling Problemmentioning

confidence: 99%

Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm

2021

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Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.

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“…Resource buffers, which are placed on the critical chain, ensure the required resource availability when needed [31]. Feeding buffers are added at the end of a non-critical chain [32] to ensure critical activities will not wait for any sub-critical activities. A project buffer, at the end of the schedule, protects against unpredictable failures, accidents, and delays [33].…”

Section: Rework Management With Ccpmmentioning

confidence: 99%

A Critical Design Structure Method for Project Schedule Development under Rework Risks

et al. 2019

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In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. Then potential criticality is proposed to measure the importance of each activity, and the rework impact area is implicated to indicate potential rework windows. Next, two methods for calculating project buffer are employed. A simulation methodology is used to verify the proposed method. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers.

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Solving the resource-constrained multi-project scheduling problem with an improved critical chain method

Cited by 15 publications

References 26 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

Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm

A Critical Design Structure Method for Project Schedule Development under Rework Risks

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