Multi-Objective Integer Programming Approaches for Solving Optimal Feature Selection Problem

Author email: yinxingxue@gmail.com
Tool name: CWMOP
Description: The optimal feature selection problem in software product line is typically addressed by the approaches based on Indicator-based Evolutionary Algorithm (IBEA). In this study we first expose the mathematical nature of this problem --- multi-objective binary integer linear programming. Then, we implement/propose three mathematical programming approaches to solve this problem at different scales. For small-scale problems (roughly less than 100 features), we implement two established approaches to find all exact solutions. For medium-to-large problems (roughly, more than 100 features), we propose one efficient approach that can generate a representation of the entire Pareto front in linear time complexity. The empirical results show that our proposed method can find significantly more non-dominated solutions in similar or less execution time, in comparison with IBEA and its recent enhancement (i.e., IBED that combines IBEA and Differential Evolution).
Bibtex: @inproceedings{10.1145/3180155.3180257, author = {Xue, Yinxing and Li, Yan-Fu}, title = {Multi-Objective Integer Programming Approaches for Solving Optimal Feature Selection Problem: A New Perspective on Multi-Objective Optimization Problems in SBSE}, year = {2018}, isbn = {9781450356381}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3180155.3180257}, doi = {10.1145/3180155.3180257}, booktitle = {Proceedings of the 40th International Conference on Software Engineering}, pages = {1231–1242}, numpages = {12}, keywords = {optimal feature selection problem, multi-objective optimization (MOO), multi-objective integer programming (MOIP)}, location = {Gothenburg, Sweden}, series = {ICSE ’18} }
Link to public pdf: https://dl.acm.org/doi/abs/10.1145/3180155.3180257
Link to tool webpage: https://sites.google.com/view/ip-method-repsol
Link to demo: Not provided by authors
Category: None
Year and Conference: 2018, ICSE
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