A Genetic Algorithm for Joint Optimization of spare Capacity and delay in Self-Healing Network


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This chapter presents the use of multi-objective Genetic Algorithms (mGA) to solve the capacity and routing assignment problem arising in the design of self-healing networks using the Virtual Path (VP) concept. Past research has revealed that Pre-planned Backup Protection method and the Path Restoration scheme can provide a good compromise on the reserved spare capacity and the failure restoration time. The aims to minimize the sum of working and backup capacity usage and transmission delay often compete and contradict with each other. Multi-objective Genetic algorithm is a powerful method for this kind of multi-objective problems. In this chapter, a multi-objective GA approach is proposed to achieve the above two objectives while a set of customer traffic demands can still be satisfied and the traffic is 100% restorable under a single point of failure. We carried out a few experiments and the results illustrate the trade-off between objectives and the ability of this approach to produce many good compromise solutions in a single run. To measure the performance of approach, our results are used to compare with that using single objective genetic algorithm (sGA).
Original languageEnglish
Title of host publicationRecent Advances in Simulated Evolution and Learning
EditorsKay Chen TAN, Meng Hiot LIM, Xin YAO, Lipo WANG
PublisherWorld Scientific
Number of pages20
ISBN (Print)9789812389527
Publication statusPublished - 2004
Externally publishedYes

Publication series

NameAdvances in Natural Computation
PublisherWorld Scientific
ISSN (Print)2010-295X


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