JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (11): 1-10.doi: 10.6040/j.issn.1671-9352.0.2017.193

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Individual strength-based multi-objective immune algorithm with adaptive differential evolution

SHI Pei-yun, GAO Xing-bao*   

  1. School of Mathematics and Information Science, Shaanxi Normal University, Xian 710119, Shaanxi, China
  • Received:2017-04-21 Online:2017-11-20 Published:2017-11-17

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Abstract: Considering that some information contained in the dominant solution may be helpful to search for the optimal solution, some nondominated solutions and dominated solutions are selected in the clone phase to enhance the diversity of population and avoid the premature. In the evolutionary phase, crossover and mutation are excuted by an adaptive differential evolution operator and population is perturbed by the polynomial mutation operator to balance effectively global and local search of the algorithm. An archive is built based on individual strength to store a number of good solutions which are evolved and updated at each iteration. The proposed algorithm is compared with five existing evolutionary algorithms on ten standard benchmark functions. Experimental results show that the proposed algorithm has superiority in convergence and distribution.

Key words: multi-objective optimization, immune algorithm, individual strength, differential evolution

CLC Number: 

  • TP301
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