An Efficient Approximate Dynamic Programming Approach for Resource-Constrained Project Scheduling with Uncertain Task Duration

Alireza Etminaniesfahani, Hanyu Gu, Leila Moslemi Naeni, Amir Salehipour

Abstract: The resource-constrained project scheduling problems (RCPSP) with uncertainties have been widely studied. The existing approaches focus on open-loop task scheduling, and only a few research studies develop a dynamic and adaptive closed-loop policy as it is regarded as computationally time-consuming. In this paper, an approximate dynamic programming (ADP) approach is developed to solve the RCPSPs with stochastic task duration (SRCPSP). The solution from a deterministic average project is utilised to reduce the computational burden associated with the roll-out policy, and a parameter is introduced in the roll-out policy to control the search strength. We test the proposed approach on 960 benchmark instances from the well-known library PSPLIB with 30 and 60 tasks and compare the results with the state-of-the-art algorithms for solving the SRCPSPs. The results show that our average-project-based ADP (A-ADP) approach provides competitive solutions in a short computational time. The invest