Author/Authors :
Sangtarash, B. H. Department of Civil Engineering - University of Sistan and Baluchestan, Zahedan, Sistan and Baluchestan, Iran , Ghasemi, M. R. Department of Civil Engineering - University of Sistan and Baluchestan, Zahedan, Sistan and Baluchestan, Iran , Ghohani Arab, H. Department of Civil Engineering - University of Sistan and Baluchestan, Zahedan, Sistan and Baluchestan, Iran , Sohrabi, M. R. Department of Civil Engineering - University of Sistan and Baluchestan, Zahedan, Sistan and Baluchestan, Iran
Abstract :
Over the past decades, several techniques have been employed to improve the applicability of the metaheuristic optimization methods. One of the solutions for improving the capability of metaheuristic methods is the hybrid of algorithms. This study proposes a new optimization algorithm called HPBA which is based on the hybrid of two optimization algorithms; Big Bang-Big Crunch (BB-BC) inspired by the theory of the universe evolution and Artificial Physics Optimization (APO) which is a physical base optimization method. Finally, the performance of the proposed optimization method is compared with the originated methods. Moreover, the performance of the proposed algorithm is evaluated for truss optimization as an applied constrained optimization problem.
Keywords :
metaheuristic methods , optimization , artificial physics optimization (APO) , big bang-big crunch (BB-BC)
