An enhanced tabu search algorithm for resource-constrained project scheduling with a flexible project structure

In this paper we consider the resource-constrained project scheduling problem with a flexible project structure and continuous activity durations. A mathematical model based on the resource-flow formulation is developed to tackle this problem. Due to the NP-hard nature of the problem, this mathematical model can only be used to find the optimal solution to small-scale problems. To address this issue, an enhanced tabu search algorithm is proposed, which utilizes an outer loop for activity selection and an inner loop for activity sequencing. The algorithm introduces several innovative features, including the integration of filtering, elite, and perturbation strategies, as well as new neighborhood operators. The parameters of the algorithm are calibrated using orthogonal experiments, and its efficacy is evaluated through extensive computational experiments conducted on multiple benchmark datasets. The results indicate that the proposed tabu search algorithm not only performs significantly better and more stable than existing metaheuristics, but also surpasses the performance of the traditional mathematical model based on rounded durations.