Resource-Constrained Project Scheduling Under Uncertainty: Models, Algorithms and Applications.

摘要

This research aims to develop new optimization models and algorithms for project scheduling under both resource constraints and uncertainties, a problem known as the stochastic resource-constrained project scheduling problem (SRCPSP) in the operations research (OR) and scheduling literature. In a typical SRCPSP, a decision-maker attempts to obtain a feasible schedule of project tasks such that: (i) their temporal/precedence relationships are satisfied; (ii) the available resource capacity is not exceeded in each time period; and (iii) the expected project makespan is minimized. Using the developed modeling and solution methodologies, it is our goal to enhance the quality of decision support for scheduling complex large-scale projects in military, manufacturing, construction and professional service sectors.