An improved trajectory-based hybrid metaheuristic applied to the noisy DNA Fragment Assembly Problem
The DNA Fragment Assembly Problem (FAP) is an NP-complete that consists in reconstructing a DNA sequence from a set of fragments taken at random. The FAP has been successfully and efficiently solved through metaheuristics. But these methods usually face difficulties to succeed when noise appears in the input data or during the search, specially in large instances. In this regard, the design of more efficient techniques are indeed necessary. One example of these techniques found in literature is the Problem Aware Local Search (PALS) which represents a state-of-the-art and robust assembler to solve noisy instances. Although PALS performs better than other metaheuristics, the quality of the achieved solutions by this method can still be improved. Towards this aim, this work proposes a new hybrid and effective method that combines a local search technique specially designed for this problem (PALS) with Simulated Annealing (SA), which is further distributed following an island model. Our proposed hybrid approach showed an improved performance on the largest non-noisy and noisy instances when compared separately with Simulated Annealing and PALS.
metaheuristic dna fragment assembly problem problem aware local search noisy instance simulated annealing parallelism