Stochastic Scheduling with Multiple Resource Constraints Using a Simulated Annealing-Based Algorithm

This paper proposes a new algorithm using Simulated Annealing (SA) for stochastic scheduling. Stochastic effects are added with nondeterministic activity durations. Simple simulated annealing can not properly handle such a complex problem so an improved version is produced and utilized within the algorithm. Generally, the availability of resources is not enough to complete all the current activities of the project and activities compete for multiple resources which stimulates considering multiple resource constraints in formulation. The superiority of the model over one of the famous heuristics is verified by a numerical example using Monte Carlo method (MC).