Optimal sub-contractor selection and allocation in a multiple construction project: Project portfolio planning in practice

Afshar, Mohammad Reza; Shahhosseini, Vahid; Sebt, Mohammad Hassan

doi:10.1080/01605682.2020.1835450

Cited by 11 publications

(9 citation statements)

References 29 publications

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“…The performance of a construction project depends on the abilities of the selected GC and SubC [27]. Given the increasing complexity and expertise of construction projects, GCs hire more SubCs for every work type, considering that SubCs play a critical role in construction projects [13,28]. The GC shares not only the profit with the SubCs but also the risks [13,15].…”

Section: Microscopic Viewpoint Analysis Of the Resource Planningmentioning

confidence: 99%

“…The selection of SubCs requires a method of presenting an appropriate decision-making standard [30]. Because the performance of a project can vary based on the selected SubCs [28,31], risks can be reduced by objectively evaluating the schedule and resource input plan suggested by the SubCs for each work type [13,32]. Therefore, it is crucial for the GC to analyze the performance of the SubCs during selection, which requires quantification for resource planning and SubC analysis [13].…”

Section: Microscopic Viewpoint Analysis Of the Resource Planningmentioning

confidence: 99%

“…Because an estimated 120 m 3 can be processed per hour by each server, there is sufficient room for processing the planned daily volume. Zones 2,4,7,9,18,19,20,21 + 22,[23][24][25][26][27][28][29], like Zone 1, comfortably allow the concrete pouring server team to handle their daily workload. ρ in zones 3, 6, and 12 is less than 1.0, indicating that stable services can be provided.…”

Section: Basic Performance Analysis In the Queueing Modelmentioning

confidence: 99%

See 2 more Smart Citations

Microscopical Resource Allocation for Large-Scale Apartment Foundation Work Using Queuing Systems

2022

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Resource management can determine the success or failure of construction projects and is indispensable in frame construction owing to the numerous resources allocated. Various research methodologies have been proposed for successful resource management, but they have not been conducted from a microscopic point of view such as activity. This paper quantitatively analyzes the impact of a concrete pouring team allocation on the project from a microscopic point of view, and proposes a framework for allocating the optimal team. Firstly, a time-dependent queueing model-based method is proposed for evaluating the influence of the pouring team for foundation concrete pouring. Data from large-scale apartment project cases in South Korea were used to verify this framework. Using time and cost metrics, the impact of the pouring team on the project was quantitatively analyzed. Finally, comparative analysis was performed to compare the concrete pouring team costs, including the average server cost and waiting cost before and after optimization. The proposed method reduced the total pouring team cost by 26.27% (KRW 35,547,600); it can help determine the optimal number of concrete pouring teams required for frame construction and improve the performance of construction projects from the process planning stage itself, by ensuring appropriate resource planning. However, since a single case was used, it is necessary to apply the proposed framework to actual construction after analyzing various cases in future studies.

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Section: Microscopic Viewpoint Analysis Of the Resource Planningmentioning

confidence: 99%

Section: Microscopic Viewpoint Analysis Of the Resource Planningmentioning

confidence: 99%

Section: Basic Performance Analysis In the Queueing Modelmentioning

confidence: 99%

See 1 more Smart Citation

Microscopical Resource Allocation for Large-Scale Apartment Foundation Work Using Queuing Systems

2022

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“…Villafáñez et al (2019) presented a generic heuristic method for solving resource-constrained multi-project scheduling problems. Afshar et al (2020a, 2020b) proposed a mixed-integer programming (MIP) model to manage subcontractors in multiple project environments such that minimize total cost. Hauder et al (2020) used mixed-integer and constrained programming models to allocate renewable resources in multiple projects.…”

Section: Multi-project Environmentmentioning

confidence: 99%

“…Finally, defuzzification is done on the output MFs to interpret the obtained results (Zadeh, 1975; Perng et al , 2005; Roghanian et al , 2018). In the following, the mathematical definitions of the fuzzy engine used in the present study are defined (Afshar et al , 2020a, 2020b).…”

Section: Justifying the Fuzzy Multi-criteria Decision-making Model Fo...mentioning

confidence: 99%

Introducing a fuzzy MCDM model for financial management in multiple project environments

Afshar

Zenozi²

2021

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Purpose Statistics in the construction industry show that lack of timely injection of funds to projects by clients is one of the common problems confronted by contractors. This problem is intensified when contractors construct multiple projects simultaneously. In these situations, it is rational that contractors share their financial resources among projects according to project conditions and the firm’s vision. This study aims to propose a fuzzy multi-criteria decision making (MCDM) model for financial management in multiple project environments. Design/methodology/approach First, the project evaluation criteria are defined using exploratory study and interviews with experts. Second, the weights of criteria are determined based on company strategies. Then, each of the projects are evaluated in each criterion. Finally, the fuzzy weighted average approach is used to determine the proportion of each project from the financial resources. Findings The proposed model is prepared as an applicable model for general contractors to assign financial recourses among the multiple projects optimally. Originality/value As a lack of applicable model assigning the financial resources among the multiple projects, this study is one of the first research studies that proposed a fuzzy MCDM model to assign financial resources to multiple projects optimally.

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A genetic algorithm for subcontractors selection and allocation in multiple building projects

2021

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In construction industry general contractors (GCs) need to manage and conduct numerous projects simultaneously. To this aim, they usually have subcontractors conduct available tasks and projects.So, subcontractor management is becoming a major challenge. To deal with this challenge, GCs aim to reduce total costs of projects including employment /subcontracting costs, indirect costs, tardiness penalties, and the money which must be paid for movement of workforce from one project to another. The aim of current research study is to propose a model for selecting subcontractors and assigning available tasks in the project to them in order to reduce the costs of the GC. Then, a genetic algorithm (GA) is proposed to solve a real problem. The proposed algorithm is innovative from three points of view: (1) generation of initial population; (2) subcontractor assignment approach and (3) the objective function. The problem was also solved by means of an exact method. Then, the results of proposed algorithm were compared to the outcomes of the exact method. This comparison shows that the proposed algorithm can efficiently help GCs select subcontractors and assign available tasks to each subcontractor when several projects must be carried out simultaneously.

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Optimal sub-contractor selection and allocation in a multiple construction project: Project portfolio planning in practice

Cited by 11 publications

References 29 publications

Microscopical Resource Allocation for Large-Scale Apartment Foundation Work Using Queuing Systems

Microscopical Resource Allocation for Large-Scale Apartment Foundation Work Using Queuing Systems

Introducing a fuzzy MCDM model for financial management in multiple project environments

A genetic algorithm for subcontractors selection and allocation in multiple building projects

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