Possibilistic Moments for the Task Duration in Fuzzy PERT

Chrysafis, Konstantinos A.; Papadopoulos, Basil K.

doi:10.1061/(asce)me.1943-5479.0000296

Cited by 14 publications

(10 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This fact does not have transcendental implications on scheduling with crisp values, but with fuzzy values the equation must be solved as a Minkowski´s subtraction (Buckley and Eslami, ; Chrysafis and Papadopoulos, ) of the supports of the fuzzy number Equation , guarantying that the obtained solution always culminates in a positive confidence interval (Gil‐Aluja, ). If a fuzzy difference is applied, negative values can be obtained for the times of the activities, providing incorrect solutions:

\begin{matrix} left {\bar{italicLS}}_{i} ((), x) \oplus {\bar{italicDur}}_{i} ((), x) = {\bar{italicLF}}_{i} ((), x) \\ left ((), l s_{i 1}, l s_{i 2}, l s_{i 3}) \oplus ((), d_{i 1}, d_{i 2}, d_{i 3}) = ((), l f_{i 1}, l f_{i 2}, l f_{i 3}) \\ left \{\begin{matrix} left l s_{i 1} = trueprefixmin ((), l s_{i 2}, l f_{i 1} - d_{i 1}) \\ left l s_{i 2} = l f_{i 2} - d_{i 2} \\ left l s_{i 3} = trueprefixmax ((), l s_{i 2}, l f_{i 3} - d_{i 3}) \end{matrix} \end{matrix}

…”

Section: The Proposed Fuzzy‐gpsp For Production Planning In Constructmentioning

confidence: 99%

See 1 more Smart Citation

The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations

Ponz-Tienda

Pellicer

Marco

et al. 2015

Computer aided Civil Eng

View full text Add to dashboard Cite

Abstract:In scheduling, estimations are affected by the imprecision of limited information on future events, and the reduction in the number and level of detail of activities. Overlapping of processes and activities requires the study of their continuity, along with analysis of the risks associated with imprecision. In this line, this paper proposes a fuzzy heuristic model for the Project Scheduling Problem with flows and minimal feeding, time and work Generalized Precedence Relations with a realistic approach to overlapping, in which the continuity of processes and activities is allowed in a discretionary way. This fuzzy algorithm handles the balance of process flows, and computes the optimal fragmentation of tasks, avoiding the interruption of the critical path and reverse criticality. The goodness of this approach is tested on several problems found in the literature; furthermore, an example of a 15-story building was used to compare the better performance of the algorithm implemented in Visual Basic for Applications (Excel) over that same example input in Primavera© P6 Professional V8.2.0, using five different scenarios.

show abstract

\begin{matrix} left {\bar{italicLS}}_{i} ((), x) \oplus {\bar{italicDur}}_{i} ((), x) = {\bar{italicLF}}_{i} ((), x) \\ left ((), l s_{i 1}, l s_{i 2}, l s_{i 3}) \oplus ((), d_{i 1}, d_{i 2}, d_{i 3}) = ((), l f_{i 1}, l f_{i 2}, l f_{i 3}) \\ left \{\begin{matrix} left l s_{i 1} = trueprefixmin ((), l s_{i 2}, l f_{i 1} - d_{i 1}) \\ left l s_{i 2} = l f_{i 2} - d_{i 2} \\ left l s_{i 3} = trueprefixmax ((), l s_{i 2}, l f_{i 3} - d_{i 3}) \end{matrix} \end{matrix}

…”

Section: The Proposed Fuzzy‐gpsp For Production Planning In Constructmentioning

confidence: 99%

“…Ponz-Tienda et al (2012) proposed a fuzzy scheduling model integrating a novel interpretation of Earned Value Indexes. The latest proposal was by Chrysafis and Papadopoulos (2014) with an alternative approach to Fuzzy-PERT based on possibilistic estimate for the mean to avoid the problem of the backward recursion.…”

Section: Literature Reviewmentioning

confidence: 99%

The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations

Ponz-Tienda

Pellicer

Marco

et al. 2015

Computer aided Civil Eng

View full text Add to dashboard Cite

show abstract

“…Chrysafis and Papadopoulos [22] made a research effort to improve the fuzzy version of the program evaluation and review technique PERT and avoid the backward recursion problem. The tools for this operation were the possibilistic moments of fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

Decision Making for Project Appraisal in Uncertain Environments: A Fuzzy-Possibilistic Approach of the Expanded NPV Method

Chrysafis

Papadopoulos

2020

Symmetry

Self Cite

View full text Add to dashboard Cite

The major drawback of the classic approaches for project appraisal is the lack of the possibility to handle change requests during the project’s life cycle. This fact incorporates the concept of uncertainty in the estimation of this investment’s worth. To resolve this issue, the authors use fuzzy numbers, possibilistic moments of fuzzy numbers and the hybrid (fuzzy statistic) fuzzy estimators’ method in order to introduce a fuzzy possibilistic version of the expanded net present value method (FPeNPV). This approach consists of two factors: the fuzzy possibilistic NPV and the fuzzy option premium. For the estimation of the fuzzy NPV, some basic assumptions are taken into consideration: (1) the opportunity cost of capital, used as the present value interest factor calculated through the weighted average cost of capital (WACC), (2) the equity cost, determined through the possibilistic set-up of the capital asset pricing model CAPM, and (3) the inflation factor, also included in the estimation of the NPV. The fuzzy estimators’ method is used for the computation of the fuzzy option premium. An algorithm of nine major steps leads to the computation of the FPeNPV. This gives the administration the opportunity to adapt to potential changes in the company’s internal and external environments. In this way, the symmetry between the planning and execution phase of a project can be reinstated. The results validate the statement that fuzzy and intelligent methods remain valuable tools to express uncertainty in various scientific areas. Finally, an illustrative example aims at a thorough comprehension of this new approach of the expanded NPV method.

show abstract

“…They proposed a multi objective nonlinear mathematical model and an algorithm for solving the problem. Some of the other recent papers in the literature are conducted by Castro-Lacouture et al [25], Afshar and Fathi [26], Shi and Gong [27], Wang and Huang [28] , Bhaskar et al [29], Ponz-Tienda et al [30], Maravas and Pantouvakis [31], Xu and Zhang [32], Masmoudi and Haït [33], Huang et al [34] , Chrysafis and Papadopoulos [35], Huang et al [36], Yu et al [37], Yousefli [38], Zohoori et al [39], Habibi et al [40] Alipouri et al [41] and Birjandi and Mousavi [42]. As seen from the literature review of this paper, fuzzy project scheduling problems have been mostly investigated with fuzzy ranking methods, fuzzy simulation, and heuristic or metaheuristic.…”

Section: Introductionmentioning

confidence: 99%

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

Arık

2019

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

View full text Add to dashboard Cite

This paper proposes a credibility based chance constrained programming approach for project scheduling problems with fuzzy activity durations where the objective is to minimize the fuzzy project completion time. This paper expresses the fuzzy events such as a project activity’s duration or project completion time with fuzzy chance constraints and the chance of a fuzzy event is illustrated with fuzzy credibility distribution. Due to uncertainty in durations of a project, fuzzy sets and fuzzy numbers can be used in order to illustrate the uncertainty and find a solution space for the problem. Therefore, fuzzy credibility based chance constraint technique is investigated for project scheduling problems with fuzzy activity durations considering the uncertainty or chance of a fuzzy event within a closed interval. In this paper, a fuzzy mathematical model and its crisp equivalent by using credibility measure and chance-constrained programming are given for project scheduling problems with fuzzy activity durations.

show abstract

Possibilistic Moments for the Task Duration in Fuzzy PERT

Cited by 14 publications

References 31 publications

The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations

The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations

Decision Making for Project Appraisal in Uncertain Environments: A Fuzzy-Possibilistic Approach of the Expanded NPV Method

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

Contact Info

Product

Resources

About