A two-stage approach for the critical chain project rescheduling

Zhao, Yan; Cui, Nanfang; Tian, Wendi

doi:10.1007/s10479-019-03347-3

Cited by 21 publications

(9 citation statements)

References 24 publications

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“…OM has been defined in literature as end-to-end organisational management activities and service chains (Karmarkar and Apte, 2007;Subramanian and Ramanathan, 2012) which comprises of several activities such as product designing, process designing, production of goods, planning, scheduling (Zhao et al, 2020), personalized targeting, delivers, customizations, logistics, outsourcing, and many more. The first research gap for the study is the gap pointed by Brock and Wangenheim (2019) that managers have very less knowledge on how to use AI in their organization's operations.…”

Section: Introductionmentioning

confidence: 99%

Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions

2020

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In this digital era, data is new oil and artificial intelligence (AI) is new electricity, which is needed in different elements of operations management (OM) such as manufacturing, product development, services and supply chain. This study explores the feasibility of AI utilization within an organization on six factors such as job-fit, complexity, long-term consequences, affect towards use, social factors and facilitating conditions for different elements of OM by mining the collective intelligence of experts on Twitter and through academic literature. The study provides guidelines for managers for AI applications in different components of OM and concludes by presenting the limitations of the study along with future research directions.

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Section: Introductionmentioning

confidence: 99%

Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions

2020

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“…The use of several distributions with other parameter estimates has been proposed (Hajdu and Bokor 2016) . Zhao et al (2020) solved the resource conflict problems by a twostage approach combined with a feeding buffer for rescheduling. Beşikci et al (2015) introduced a multi-project planning environment which included several projects with specific dates.…”

Section: Scheduling Methodsmentioning

confidence: 99%

Project scheduling and buffer management: A comprehensive review and future directions

Zohrehvandi¹,

Soltani²

2022

10.5267/j.jpm

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In the project management, buffers are considered to handle uncertainties that lead to changes in project scheduling which in turn causes project delivery delay. The purpose of this survey is to discuss the state of the art on models and methods for project buffer management and time optimization of construction projects and manufacturing industries. There are not literally any surveys which review the literature of project buffer management and time optimization. This research adds to the previous literature surveys and focuses mainly on papers after 2014 but with a quick review on previous works. This research investigates the literature from project buffer sizing, project buffer consumption monitoring and project time/resource optimization perspectives.

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“…Zarghami et al [27] introduced a new buffer sizing method by modeling the CCPM method through a project resource reliability analysis. Zhao et al [28] proposed a buffer sizing method that considered resource interference in critical chain project management. Zohrehvandi et al [29] introduced an efficient project buffer and resource management (PBRM) model for project resource leveling and project buffer sizing and controlling of project buffer consumption of a wind power plant project to achieve a more realistic project duration.…”

Section: Literature Reviewmentioning

confidence: 99%

A Project-Scheduling and Resource Management Heuristic Algorithm in the Construction of Combined Cycle Power Plant Projects

Zohrehvandi

2022

Computers

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Given the growing number of development projects, proper project planning and management are crucial. The purpose of this paper is to introduce a heuristic algorithm for scheduling a power plant project construction and project resource management to determine the size of project buffers and feeding buffers. This algorithm consists of three steps: 1. estimating the duration of project activities; 2. determining the size of the project buffer and feeding buffers; and 3. simulating the mentioned algorithm, which will be explained below. Innovations of this research are as follows: estimating the exact duration of project activities by using a heuristic algorithm, in addition to determining the buffer size; calculating both project buffer and feeding buffers; and applying the algorithm to implement an ACC used in combined cycle power plant projects as a numerical example. In order to evaluate the proposed algorithm, inputs from this project were run through several algorithms recently presented. The results showed that a suitable amount of buffers can be allocated for projects using this algorithm.

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A two-stage approach for the critical chain project rescheduling

Cited by 21 publications

References 24 publications

Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions

Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions

Project scheduling and buffer management: A comprehensive review and future directions

A Project-Scheduling and Resource Management Heuristic Algorithm in the Construction of Combined Cycle Power Plant Projects

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