A new algorithm for mixed-discrete design optimization

Singiresu S. Rao, Ying Xiong

Research output: Contribution to journalConference articlepeer-review


A new procedure, based on the modification of the genetic algorithm, is presented for the solution of mixed-discrete nonlinear design optimization. In this approach, the genetic algorithm is used mainly to determine the optimal feasible region containing the global optimum point, and he hybrid negative sub-gradient or Polak-Ribiere-Poiyak (PRP) conjugate gradient method, combined with discrete one-dimension search, is subsequently used to replace the GA to find the final optimum solution. The modified genetic algorithm can improve the convergence speed and computational efficiency compared with other GAs or random search methods. Several practical examples of mechanical design are tested using the computer program developed. The numerical results demonstrate the effectiveness and robustness of the proposed approach.

ASJC Scopus subject areas

  • Architecture
  • Materials Science(all)
  • Aerospace Engineering
  • Mechanics of Materials
  • Mechanical Engineering


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