References

1. P1

1.1. M. Harman, W. B. Langdon, Y. Jia, D. R. White, A. Arcuri, and J. A. Clark. The gismoe challenge: Constructing the pareto program surface using genetic programming to find better programs (keynote paper). In Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering, pages 1–14. ACM, 2012.

2. P2

2.1. S. A. Ludwig. Applying particle swarm optimization to quality-of-servicedriven web service composition. In Advanced Information Networking and Applications (AINA), 2012 IEEE 26th International Conference on, pages 613–620. IEEE, 2012.

3. P3

3.1. Z. Michalewicz and D. B. Fogel. How to solve it: modern heuristics. Springer Science & Business Media, 2013.

4. P4

4.1. D. R. White, A. Arcuri, and J. A. Clark. Evolutionary improvement of programs. Evolutionary Computation, IEEE Transactions on, 15(4):515– 538, 2011.

5. P5

5.1. B. R. Bruce, J. Petke, and M. Harman. Reducing energy consumption using genetic improvement. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, pages 1327–1334. ACM, 2015.

6. P6

6.1. M. Harman and J. Petke. Gi4gi: Improving genetic improvement fitness functions. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference, pages 793–794. ACM, 2015.

7. P7

7.1. S. O. Haraldsson and J. R. Woodward. Automated design of algorithms and genetic improvement: contrast and commonalities. In Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pages 1373–1380. ACM, 2014.

8. P8

8.1. I. Meedeniya, A. Aleti, B. Bühnova, et al. Redundancy allocation in automotive systems using multi-objective optimisation. In Symposium of Avionics/Automotive Systems Engineering (SAASE’09), San Diego, CA, 2009.

9. P9

9.1. A. G. Millard, D. R. White, and J. A. Clark. Searching for pareto-optimal randomised algorithms. In Search Based Software Engineering, pages 183– 197. Springer, 2012.