Friday, 11:30 - 11:55 h, Room: H 2032


Marco Boschetti
A Lagrangian heuristic for the sprint planning in agile methods

Coauthors: Turricchia Elisa, Golfarelli Matteo, Rizzi Stefano, Maniezzo Vittorio


Agile methods have been adopted by an increasing number of companies to make software development faster and nimbler. Most 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, e.g., the estimated complexity, business value, and affinity of the user stories (functionalities) included in each sprint, which makes the planning problem difficult.
We present an approach for the sprint planning in agile methods based on a MIP model. Given the estimates made by the project team and a set of development constraints, the optimal solution is a sprint plan that maximizes the business value perceived by users.
Solving to optimality the model by a MIP solver (e.g., IBM Ilog Cplex) takes time and for some instances even to find a feasible solution requires too large computing times for an operational use. For this reason we propose a Lagrangian heuristic based on a relaxation of the proposed model and some greedy algorithms. Computational results on both real and synthetic projects show the effectiveness of the proposed approach.


Talk 3 of the invited session Fri.1.H 2032
"Matheuristics" [...]
Cluster 11
"Integer & mixed-integer programming" [...]


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