A novel improved parallel hybrid immune algorithm for the solution to packing and layout problems. (1st January 2012)

• Record Type: Journal Article
• Authors: Zhao, Feng-Qiang; Li, Guang-Qiang; Du, Jia-Lu; Guo, Chen
• Is Part Of: International journal of wireless and mobile computing. Volume 5:Number 2(2012)
• Page Start: 199
• Page End: 205
• Publication Date: 2012-01-01
• Subjects: hybrid immune algorithm -- genetic algorithms -- swarm intelligence -- layout; Mobile computing -- Periodicals; Wireless communication systems -- Periodicals; 004.6
• DOI: 10.1504/IJWMC.2012.046782
• Languages: English
• ISSNs: 1741-1084

Abstract

Packing and layout problems belong to NP-complete problems theoretically and they have extensive engineering application practically. The algorithms based on swarm intelligence are relatively effective to solve this kind of problems. But usually there still exist two main defects of them, i.e. premature convergence and slow convergence rate. To overcome these defects, a novel Improved Parallel Hybrid Immune Algorithm (IPHIA) is proposed based on Parallel Genetic Algorithms (PGA). The global performance of the proposed algorithm is improved by introducing immunity principle into PGA and it is mainly embodied in two aspects. One is that the immune selection operator based on interpolating rank-based selection with pressure can prevent the algorithm from premature. The other is that convergence rate can be accelerated by individual migration strategy between subpopulations based on immune memory mechanism. In this algorithm, multiple subpopulations evolution based on adaptive crossover and mutation are adopted. To be hybridised with complex method can further improve local searching performance of the algorithm. An example of packing and layout problems shows that IPHIA is feasible and effective.