Reactive project scheduling with information handling cost

Reducing uncertainty through reasonable investment in information handling is very essential for efficient implementation of project under uncertain conditions. In this paper, the reactive project scheduling problem with information handling cost is studied. The objective is to minimize the uncertain cost of project by deciding on the optimal investment in information handling. Firstly, the functional relationship between standard deviation of activity duration and information handling cost is abstracted. Then, the optimization model of problem is constructed and a property of the model is refined. For the NPhardness of the studied problem, the heuristic algorithms of tabu search (TS), variable neighborhood search (VNS) and their mixed version (TVNS) are developed. Ultimately, the algorithms are tested on a randomly generated standard instances set, and the effects of several key parameters on the optimization objective are analyzed. The results show that the TVNS is better than the other two algorithms in performance, and its search efficiency is effectively improved by the improvement measure based on the property. The uncertainty cost of project decreases with the increase of the influence coefficient of information handling and the resource strength, and increases with the increase of activity weight.