TRUSS SIZING OPTIMIZATION USING ENHANCED DIFFERENTIAL EVOLUTION WITH OPPOSITION-BASED MUTATION AND NEAREST NEIGHBOR COMPARISON

Abstract

An optimization algorithm based on differential evolution (DE) is presented for optimal truss sizing design. The algorithm applies a simple opposition-based mutation scheme and the so-called nearest neighbor comparison method to the classical DE. The opposition-based mutation can accelerate the convergence, while the nearest neighbor comparison, which uses neighborhood information to judge the order relation between two solution points, can omit an unfavorable solution without evaluating it. Four well-known truss sizing problems with continuous variables are used to examine the performance of the proposed algorithm. The results show that the new DE algorithm can effectively obtain high quality solutions and it is competitive to some modern metaheuristic algorithms in the literature.

Keywords: Truss sizing optimization; differential evolution; opposition-based method; nearest neighbor comparison.

Received: September 9^th, 2016, revised: September 23^th, 2016, accepted: October 13^th, 2016