Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Process-Centered Requirements Engineering
Process-Centered Requirements Engineering
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Using Genetic Algorithms in Engineering Design Optimization with Non-Linear Constraints
Proceedings of the 5th International Conference on Genetic Algorithms
On the Performance Assessment and Comparison of Stochastic Multiobjective Optimizers
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Implementing requirements traceability: a case study
RE '95 Proceedings of the Second IEEE International Symposium on Requirements Engineering
Requirements interaction management
ACM Computing Surveys (CSUR)
An Industrial Survey of Requirements Interdependencies in Software Product Release Plannin
RE '01 Proceedings of the Fifth IEEE International Symposium on Requirements Engineering
Engineering and Managing Software Requirements
Engineering and Managing Software Requirements
Constraint handling in genetic algorithms using a gradient-based repair method
Computers and Operations Research
Search--based approaches to the component selection and prioritization problem
Proceedings of the 8th annual conference on Genetic and evolutionary computation
The multi-objective next release problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
StakeNet: using social networks to analyse the stakeholders of large-scale software projects
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Today/future importance analysis
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Search Based Optimization of Requirements Interaction Management
SSBSE '10 Proceedings of the 2nd International Symposium on Search Based Software Engineering
Using Interactive GA for Requirements Prioritization
SSBSE '10 Proceedings of the 2nd International Symposium on Search Based Software Engineering
Ant Colony Optimization for the Next Release Problem: A Comparative Study
SSBSE '10 Proceedings of the 2nd International Symposium on Search Based Software Engineering
A study of the bi-objective next release problem
Empirical Software Engineering
Comparison between lamarckian and baldwinian repair on multiobjective 0/1 knapsack problems
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A Generic Framework for Constrained Optimization Using Genetic Algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Software Engineering
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Context: Requirements optimization has been widely studied in the Search Based Software Engineering (SBSE) literature. However, previous approaches have not handled requirement interactions, such as the dependencies that may exist between requirements, and, or, precedence, cost- and value-based constraints. Objective: To introduce and evaluate a Multi-Objective Search Based Requirements Selection technique, using chromosome repair and to evaluate it on both synthetic and real world data sets, in order to assess its effectiveness and scalability. The paper extends and improves upon our previous conference paper on requirements interaction management. Method: The popular multi-objective evolutionary algorithm NSGA-II was used to produce baseline data for each data set in order to determine how many solutions on the Pareto front fail to meet five different requirement interaction constraints. The results for this baseline data are compared to those obtained using the archive based approach previously studied and the repair based approach introduced in this paper. Results: The repair based approach was found to produce more solutions on the Pareto front and better convergence and diversity of results than the previously studied NSGA-II and archive-based NSGA-II approaches based on Kruskal-Wallis test in most cases. The repair based approach was also found to scale almost as well as the previous approach. Conclusion: There is evidence to indicate that the repair based algorithm introduced in this paper is a suitable technique for extending previous work on requirements optimization to handle the requirement interaction constraints inherent in requirement interactions arising from dependencies, and, or, precedence, cost- and value-based constraints.