Project scheduling based on resource leveling using fuzzy ranking and genetic algorithm

Project planning and scheduling is often addressed in the paradigm of combined fuzzy optimization, which largely owing to inherent features combination ensuing uncertainty determining variables, none more significant than timetables deadlines activities. As such, purpose current study present a novel metaheuristic model for aforementioned problem by applying ranking genetic algorithm on resource leveling indicator. This method will be case-studied numbers needed express uncertain variables real world. using approach paramount significance industry, as it has shown greatly ensure proper effective use resources. research seeks propose new project timetable activities levelling are examined at same time. To generate initial population algorithm, parallel prioritization used optimally level resources, while theory further employed duration