in this research, both resource allocation and reactive resource allocation problems in multi-server dynamic pert networks are analytically modeled, where new projects are expected to arrive according to a poisson process, and activity durations are also known as independent random variables with exponential distributions. such system is represented as a queuing network, where multi servers at ...

A multi-condition multi-objective optimization method that can find Pareto front over a defined condition space is developed for the first time using deep reinforcement learning. Unlike conventional methods which perform at single condition, present learns correlations between conditions and optimal solutions. The exclusive capability of examined in solutions novel modified Kursawe benchmark pr...

the paper presents a multi-factor decision-making approach for prioritizing failure modes as an alternative to traditional approach of failure mode and effect analysis (fmea). the approach is based on the ‘technique for order preference by similarity to ideal solution’ (topsis). the priority ranking is formulated on the basis of six parameters (failure occurrence, non-detection, maintainability...