A parallel cooperative team of multiobjective evolutionary algorithms for motif discovery

作者：Gonzalez Alvarez David L^*; Vega Rodriguez Miguel A

来源：Journal of Supercomputing, 2013, 66(3): 1576-1612.

DOI：10.1007/s11227-013-0951-6

• Parallel cooperative team
• OpenMP
• Evolutionary algorithm
• Motif discovery
• Multiobjective optimization

When solving a wide range of complex scenarios of a given optimization problem, it is very difficult, if not impossible, to develop a single technique or algorithm that is able to solve all of them adequately. In this case, it is necessary to combine several algorithms by applying the most appropriate one in each case. Parallel computing can be used to improve the quality of the solutions obtained in a cooperative algorithms model. Exchanging information between parallel cooperative algorithms will alter their behavior in terms of solution searching, and it may be more effective than a sequential metaheuristic. For demonstrating this, a parallel cooperative team of four multiobjective evolutionary algorithms based on OpenMP is proposed for solving different scenarios of the Motif Discovery Problem (MDP), which is an important real-world problem in the biological domain. As we will see, the results show that the application of a properly configured parallel cooperative team achieves high quality solutions when solving the addressed problem, improving those achieved by the algorithms executed independently for a much longer time.

• 出版日期2013-12