Multi-sprint planning and smooth replanning: An optimization model

Most agile methods divide a project into sprints (iterations), and include a sprint planning phase that is critical to ensure the project success. Several factors impact on the optimality of a sprint plan, which makes the planning problem difficult. In this paper we formalize the planning problem and propose an optimization model that, given the estimates made by the project team and a set of development constraints, produces a multi-sprint optimal plan that maximizes the business value perceived by users. To cope with the inherent flexibility and uncertainty of agile projects, our approach ensures that a baseline plan can be revised and re-optimized during project execution without disrupting it, which we call smooth replanning. The planning problem is converted into a generalized assignment problem, given a linear programming formulation, and solved using the IBM ILOG CPLEX Optimizer. Our model is validated on both real and synthetic projects. In particular, a case study on two real projects confirms the effectiveness of our approach; as to efficiency, for medium-sized problems an exact solution is found in a few minutes, while for large problems a heuristic solution that is less than 1% far from the exact one is returned in a few seconds. Finally, some smooth replanning tests investigate the trade-off between plan quality and stability.