Solving the resource-constrained project scheduling problem using filter-and-fan approach

The resource-constrained project scheduling problem is a notoriously difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms to find optimal or near-optimal solutions. This paper proposes a new heuristic algorithm for this problem based on filter-and-fan method incorporated with a local search, exploring in the defined neighborhood space. In the algorithm, the local search is used to generate a starting solution as well as to re-optimize the best schedules produced by the filter-and-fan method. The filter-and-fan is itself a local search procedure that generates compound moves in a tree search fashion. Computational results applied on a standard set of 2040 benchmark problems from the literature demonstrate the effectiveness of the approach.