Toward a scalable type-2 fuzzy model for resource-constrained project scheduling problem

Abstract

This paper develops a scalable method for the Resource-Constrained Project Scheduling Problem (RCPSP) with a type-2 fuzzy uncertain activity time-span. The objective of this method is the project completion time minimization. This problem has been solved through a scalable type-2 fuzzy Dijkstra algorithm inside different activities rules. The Dijkstra algorithm produces a different permutation of activities alongside each selected path that should be examined in optimization function using the type-2 fuzzy simplex algorithm. This method generates the best permutation using run-time optimization which significantly satisfies lower project completion time inside the project cost minimization. Also, the method proposed a resource workload for both tactical and operational levels of planning. The presented approach is conducted by the gas-related industry project and a case on satellite design of the aerospace industry on 3 different Resource/Process/Environment strategies. The results convey the defined method has a better performance compared to type-1 fuzzy for covering the largest uncertainty domain. This method could be considered in every engineering project management.