A comment on solving project-scheduling problems with a heuristic learning algorithm

Article review on 'Solving project-scheduling problems with a heuristic learning algorithm' by R. Zamani and L-Y Shue, Journal of the Operational Research Society, volume 49, pages 709-716 -- In their recent paper, Zamani and Shue describe Search and Learn A* (SLA*) algorithm with an implementation method for solving resource-constrained project scheduling (RCPS) problems. The algorithm is an improvement over Learning Real Time A*. The contributions of SLA* are the complete heuristic learning process with backtracking and use of updated heuristic estimate in the same originating state. The authors claim that the algorithm is able to find an optimal solution by enumerating the promising search paths in a single solving trial. In support of the proof of solution optimality, only one benchmark RCPS problem is solved with a theoretical proof in the appendix. However, a more detailed computational investigation is lacking to establish the fact of optimality and to broaden the scope of application