A study of project scheduling optimization using Tabu Search algorithm

The research will focus on investigating a more efficient alternative to solve resource-constrained project scheduling problems (RCPSP). Also, instead of using traditional Tabu Search (TS) algorithm and the other Artificial Intelligence (AI)-based heuristic approaches, this research develops an improved TS model by modifying the way of finding a starting solution instead of traditional TS algorithm to solve the problems described above. The model can effectively provide better results in reducing project duration for solving RCPSP compared to traditional TS-based search techniques and Artificial Intelligence (AI)-based approaches. The paper suggests the optimum parameters’ setting values for the models the paper presented through sensitivity analysis to obtain better solution quality more easily. Also, the method the paper presented provides a good user interface linking with existing commercial software systems to help for the practitioner in the application of project management in the real world.