On the specificity of a possibility distribution
Fuzzy Sets and Systems
A Net Practice for Software Project Management
IEEE Software
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
New stochastic models for capacitated location-allocation problem
Computers and Industrial Engineering
Parallel machine scheduling models with fuzzy processing times
Information Sciences—Informatics and Computer Science: An International Journal
Applying fuzzy method for measuring criticality in project network
Information Sciences: an International Journal
Project Scheduling Problem for Software Development with Random Fuzzy Activity Duration Times
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
A robust scheduling method based on a multi-objective immune algorithm
Information Sciences: an International Journal
Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
An efficient hybrid algorithm for resource-constrained project scheduling
Information Sciences: an International Journal
Criticality analysis of activity networks under interval uncertainty
Journal of Scheduling
Information Sciences: an International Journal
On the sure criticality of tasks in activity networks withimprecise durations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
Parallel-machine scheduling to minimize makespan with fuzzy processing times and learning effects
Information Sciences: an International Journal
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In this study, we introduce a Fuzzy Time-dependent Project Scheduling Problem (FTPSP), in which activity duration times are represented in the form of fuzzy sets. The duration times are considered to be time-dependent as well. Under these circumstances, the resulting FTPSP becomes far more complex when compared with the existing project scheduling problems. The complexity stems from the fact of computing the completion time of the entire project, a core issue when dealing with project scheduling problems. We first elaborate on the difficulties with the computing of the completion time. Subsequently, we develop a computational formula for estimating the overall completion time of FTPSP. Next, we formulate the FTPSP and propose three fuzzy programming models to address various requirements arising within this framework. The proposed models are handled through techniques that combine mechanisms of fuzzy simulation and genetic optimization. In this setting, fuzzy simulation is exploited to estimate the value of uncertain functions that do not exist in conventional certain project scheduling problems. Numerical experiments are included to illustrate the effectiveness of the algorithm.