Measuring schedule uncertainty for a stochastic resource-constrained project using scenario-based approach with utility-entropy decision model

Tseng, Ching-Chih; Ko, Po-Wen

doi:10.1080/21681015.2016.1172522

Cited by 11 publications

(11 citation statements)

References 30 publications

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“…For better understanding, the key steps of Algorithm 2 (steps 18 to 22) are further explained with an example. Assume that, due to the first disruption event at time t = 10, the set of affected and unaffected activities of a project with 7 tasks are: I af f ected = [4,5,6,7] and I unaf f ected = [1,2,3]. Now, after executing step 13, the affected activities are sorted based on their descending order of rt i , and it becomes 6−4−5−7.…”

Section: ) Modified Neh Heuristicmentioning

confidence: 99%

“…The project also faces a disruption since after executing 2 units of time, the actual duration of the activity 2 is changed from 8 units to 3 units of time and its resource consumption is decreased from 4 units to 1 unit. The actual activity durations for the execution phase are [0, 6,4,6,3,8,3,0]. The makespan for real-time approach is 44 (sequence: 1-2-4-3-5-6-7-8) which is equal to the makespan obtain for the right shifting approach.…”

Section: F Proposed Igfbid For Rcpspds (Managing Disruption)mentioning

confidence: 99%

“…Due to the dynamic behaviour of real-world environments, it is not useful to consider fixed resource capacities and stable activity durations throughout any typical project's tenure. Consequently, an important type of RCPSP is the stochastic RCPSP (SRCPSP), which is defined as a problem that involves scheduling project activities with uncertain durations, in order to achieve a predefined objective, such as to mini-mize expected project makespan, minimize project schedule instability, or minimize some other predefined objective, subject to precedence constraints and renewable resource constraints [3]. In addition to stochastic or uncertain durations, resource requests and capacities may likewise not be constant during a project's life.…”

Section: Introductionmentioning

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: ) Modified Neh Heuristicmentioning

confidence: 99%

Section: F Proposed Igfbid For Rcpspds (Managing Disruption)mentioning

confidence: 99%

Section: Introductionmentioning

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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“…In a recent study, Ref. [ 10 ] measure the uncertainty related to the evolution of a resource-constrained project scheduling problem with uncertain activity durations using the entropy concept. Ref.…”

Section: Managing Projectsmentioning

confidence: 99%

A Statistical Method for Estimating Activity Uncertainty Parameters to Improve Project Forecasting

Vanhoucke

Batselier

2019

Entropy

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Just like any physical system, projects have entropy that must be managed by spending energy. The entropy is the project’s tendency to move to a state of disorder (schedule delays, cost overruns), and the energy process is an inherent part of any project management methodology. In order to manage the inherent uncertainty of these projects, accurate estimates (for durations, costs, resources, …) are crucial to make informed decisions. Without these estimates, managers have to fall back to their own intuition and experience, which are undoubtedly crucial for making decisions, but are are often subject to biases and hard to quantify. This paper builds further on two published calibration methods that aim to extract data from real projects and calibrate them to better estimate the parameters for the probability distributions of activity durations. Both methods rely on the lognormal distribution model to estimate uncertainty in activity durations and perform a sequence of statistical hypothesis tests that take the possible presence of two human biases into account. Based on these two existing methods, a new so-called statistical partitioning heuristic is presented that integrates the best elements of the two methods to further improve the accuracy of estimating the distribution of activity duration uncertainty. A computational experiment has been carried out on an empirical database of 83 empirical projects. The experiment shows that the new statistical partitioning method performs at least as good as, and often better than, the two existing calibration methods. The improvement will allow a better quantification of the activity duration uncertainty, which will eventually lead to a better prediction of the project schedule and more realistic expectations about the project outcomes. Consequently, the project manager will be able to better cope with the inherent uncertainty (entropy) of projects with a minimum managerial effort (energy).

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“…Initially, priority list are generated by a GRASP algorithm, and subsequently, the precedence constraints are created by a GA. Recently, in 2016, Tseng and Ko (2016) presented a two-stages procedure: in the first stage, a scenario tree is generated, and in the second stage, the worst branches are eliminated using the Expected Utility-Entropy criteria.…”

Section: Special Procedures Based On Stage-by-stage Analysismentioning

confidence: 99%

The project scheduling problem with non-deterministic activities duration: A literature review

Pimiento

Serna

2018

JIEM

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Abstract:Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration.Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved.Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends.Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.

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Measuring schedule uncertainty for a stochastic resource-constrained project using scenario-based approach with utility-entropy decision model

Cited by 11 publications

References 30 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

A Statistical Method for Estimating Activity Uncertainty Parameters to Improve Project Forecasting

The project scheduling problem with non-deterministic activities duration: A literature review

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