Robust next release problem: handling uncertainty during optimization

@article{Li2014RobustNR,
  title={Robust next release problem: handling uncertainty during optimization},
  author={Lingbo Li and Mark Harman and Emmanuel Letier and Yuanyuan Zhang},
  journal={Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation},
  year={2014}
}
  • Lingbo Li, M. Harman, Yuanyuan Zhang
  • Published 12 July 2014
  • Computer Science
  • Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation
Uncertainty is inevitable in real world requirement engineering. It has a significant impact on the feasibility of proposed solutions and thus brings risks to the software release plan. This paper proposes a multi-objective optimization technique, augmented with Monte-Carlo Simulation, that optimizes requirement choices for the three objectives of cost, revenue, and uncertainty. The paper reports the results of an empirical study over four data sets derived from a single real world data set… 

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Robust Optimization - A Comprehensive Survey