@article{Cai_Wei_Huang_2012, title={Evolutionary Approaches for Multi-Objective Next Release Problem}, volume={31}, url={https://www.cai.sk/ojs/index.php/cai/article/view/1108}, abstractNote={In software industry, a common problem that the companies face is to decide what requirements should be implemented in the next release of the software. This paper aims to address the multi-objective next release problem using search based methods such as multi-objective evolutionary algorithms for empirical studies. In order to achieve the above goal, a requirement-dependency-based multi-objective next release model (MONRP/RD) is formulated firstly. The two objectives we are interested in are customers’ satisfaction and requirement cost. A popular multi-objective evolutionary approach (MOEA), NSGA-II, is applied to provide the feasible solutions that balance between the two objectives aimed. The scalability of the formulated MONRP/RD and the influence of the requirement dependencies are investigated through simulations as well. This paper proposes an improved version of the multi-objective invasive weed optimization and compares it with various state-of-the-art multi-objective approaches on both synthetic and real-world data sets to find the most suitable algorithm for the problem.}, number={4}, journal={COMPUTING AND INFORMATICS}, author={Cai, Xinye and Wei, Ou and Huang, Zhiqiu}, year={2012}, month={Oct.}, pages={847–875} }