A computational experiment to explore better robustness measures for project scheduling under two types of uncertain environments

Ma, Zhiqiang; Demeulemeester, Erik; He, Zhengwen; Wang, Nengmin

doi:10.1016/j.cie.2019.04.014

Cited by 36 publications

(17 citation statements)

References 32 publications

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“…Similar conclusions can be drawn from other review papers by Habibi, et al [44] and Kolisch and Hartmann [45]. Nature inspired metaheuristic algorithms such as (GA) [46], PSO [47], fruit-fly optimization algorithm [48] and SA [49] are a few of many approaches for solving SRCPSPs or uncertainty-based PSPs.…”

Section: A Existing Research On Srcpspsupporting

confidence: 77%

“…Ma, et al [46] propose a proactive RCPSP policy after considering both stochastic resource availabilities and stochastic activity durations. They have emphasised the need to include time buffers based on uniform distributions, particularly if there is any chance of unreliable resource availability during project tenure.…”

Section: B Research On Rcpsp With Disruptions (Rcpspd)mentioning

confidence: 99%

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Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach

2021

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Resource constrained project scheduling problems (RCPSPs) are complex optimization problems that aim to minimize project completion time after considering limited resources and precedencerelated activities with known durations. However, due to the dynamic nature of real-world applications, activity durations are vulnerable to change. In addition, resource demands along with resource availability at any stage of a project can also vary due to disruptions, which compel practitioners to rethink existing scheduling methodologies. Consequently, to mitigate the conjoint effect of those uncertainties and/or disruptions, this paper proposes a real-time reactive scheduling approach. To deal with uncertain activity durations, a chance constrained based approach is followed, which is later solved by an advanced metaheuristic based approaches called IGFBIS and IGFBID. After solving an exhaustive list of stochastic RCPSP instances, this paper proves the efficacy of the proposed approaches, which is proven to be more useful to mitigate uncertainty or disruption while executing real-life projects. INDEX TERMS Scheduling Real-life projects, project scheduling with uncertainty and disruption, Iterated greedy algorithm, Chance constrained approach

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Section: A Existing Research On Srcpspsupporting

confidence: 77%

Section: B Research On Rcpsp With Disruptions (Rcpspd)mentioning

confidence: 99%

Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach

2021

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“…In the proposed problem, the optimized objective is to maximize solution robustness 𝑅𝑜𝑏𝑢. Referred to [7]…”

Section: Problem Formulationmentioning

confidence: 99%

“…Equation ( 6) ensures that the duration of all the subactivities of activity 𝑖 must equal the expected duration of activity 𝑖. The constraints (7) guarantee that the number of splitting for a given divisible activity is no more than a predefined level called 𝜂 𝑖 , while in (8) the duration of each subactivity must be no smaller than its minimum continuous execution time. The inequalities in (9) represent the relationship between the variables 𝑥 𝑖 𝑣 ,𝑗 𝑓 ,𝑘 and 𝑦 𝑖 𝑣 ,𝑗 𝑓 ,𝑘 .…”

Section: Problem Formulationmentioning

confidence: 99%

Proactive Project Scheduling With Activity Splitting and Resource Transfer Times Under Uncertain Environments

Ning

Wang

2022

IEEE Access

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Proactive project scheduling aims to generate robust baseline schedules that are protected against the potential schedule disruptions during project execution. In this paper, we propose a new problem named the proactive resource-constrained project scheduling problem with activity split-ting and resource transfer times, and try to investigate the trade-off between the benefits of activity splitting and the drawbacks of the resulting more resource transfer times. The proposed problem is formulated into an integer programming model with considering the constraints of a maximum allowed number of splitting and a minimum period of continuous execution. Since the problem is NP-hard in the strong sense, a genetic algorithm is then developed for problem solving. From the obtained results of a designed computational experiment, we prove that the developed genetic algorithm is effective in solving the defined problem, and the benefits of activity splitting to schedule robustness improvement can be weaken with the resulting more resource transfer times among the subactivities. Besides, with the increase of the maximum allowed number of activity splitting, the decrease of the minimum continuous execution time, the decrease of resource transfer times, and the extension of project deadlines, schedule robustness increases.

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“…Gonzalez-Ruiz et al, 2019 proposed a Stochastic Fuzzy Logistic Model for patterning the construction of integrated mutilates scenarios in the financing of infrastructure projects. Ma, Demeulemeester, He, and Wang, 2019 addressed the proactive resource-constrained project scheduling problem, for exploring the better surrogate robustness measures to generate robust baseline schedules under uncertain platforms.…”

Section: Introductionmentioning

confidence: 99%

Bazı Temel İnşaat Faaliyetlerinin Olasılık Dağılımlarının Alınmasına İlişkin Örnek Olay

Gürbüz¹,

Dinç²,

Erdinç³

2020

European Journal of Science and Technology

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Under the title 'Management', it should be considered many things simultaneously such as time, money, manpower, machinery and equipment and their interactions. After that consideration, it should have also optimized them to improve the workflow, scheduling, resource usage etc. Well, it is not easy in the uncertain environment of construction sector, which has a many stakeholder, has long completion times and is highly dependent on the human labor. It is necessary to model this uncertainty. Most importantly, we need the probability data for these models. In this study a housing project consisting of 13 floors was analyzed, the completion times of 20 activities are given for each of these floors and the distribution of the duration of each activity implemented on each floor was obtained. Those activities are repeated 13 times by the same team and with the same equipment. According to that results, activities mainly fit the Logistic, Log Logistic, Lognormal and Weibull distribution. After determining that which distribution for the activities is best suited to our data, the real time data is adjusted to this distribution and the average completion time of this activity for this building is obtained. Based on the average completion time of each activity, the completion time of the entire building was obtained. The aim was getting the stochastic data from a real project to use in different management stage in future. Besides, the number of samples will also be increased and the deviations in the resulting distributions and their causes will be examined.

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A computational experiment to explore better robustness measures for project scheduling under two types of uncertain environments

Cited by 36 publications

References 32 publications

Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach

Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach

Proactive Project Scheduling With Activity Splitting and Resource Transfer Times Under Uncertain Environments

Bazı Temel İnşaat Faaliyetlerinin Olasılık Dağılımlarının Alınmasına İlişkin Örnek Olay

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