Parallel artificial fish swarm algorithm based on MPI for multidimensional 0–1 knapsack

Abstract

Artificial Fish Swarm Algorithm(AFSA) is a kind of swarm intelligence optimization algorithm. Compared with other swarm intelligence methods, such as ant colony algorithm, AFSA introduces some parameters to effectively avoid prematurely falling into local extreme. So it is often used to solve combinatorial optimization problems. The multidimensional 0-1 knapsack problem as a representative of combinatorial optimization problems, is very comment in engineering tasks and is also very complex. Using basic AFSA to solve the multidimensional 0-1 knapsack problem can achieve good results when the data is small. However, when the data scale of the problem becomes larger and the dimension increases, it is difficult to meet the actual requirements in time. In this paper the idea of using the parallel artificial fish swarm algorithm based on MPI to solve the multidimensional 0-1 knapsack is proposed and realized. Through the analysis of the experimental results, it shows that the parallel algorithm can effectively shorten the processing time and has practical value.