Island Injection Genetic Algorithm with Relaxed Coordination for the Multiple Sequence Alignment Problem
Multiple sequence alignment (MSA) is an important problem in Bioinformatics since it is often used to identify evolutionary relationships and predict secondary/tertiary structure, among others. MSAs are usually scored with the Sum-of-Pairs (SP) function and the exact SP MSA is known to be NP-Hard. Therefore, heuristic methods are used to tackle this problem. In this chapter, we propose and evaluate a parallel island injection genetic algorithm to solve the MSA problem. Unlike the other strategies, our parallel solution uses two types of interconnected archipelagoes, each with distinct types of individuals. Also, we added a relaxed coordination mechanism among the archipelagoes that contributes to reduce the execution time of our strategy. The results obtained with real protein data sets show that our strategy is able to obtain better results, when compared to the traditional island model. Also, we were able to reduce considerably the execution time, when compared to the sequential version.
KeywordsGenetic Algorithm Execution Time Good Individual Island Model Parallel Genetic Algorithm
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