Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah

Ali, Sadollah (2013) Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah. PhD thesis, University of Malaya.

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Abstract

Metaheuristic algorithms have been extensively used in numerous domains especially in engineering. The reason is that for solving complex optimization problems, classical and traditional techniques may not efficiently find global optimum solution. In this thesis, the applications of a number of well-known metaheuristic algorithms for solving engineering problems have been considered. In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). The fundamental concepts and ideas for MBA are derived from the explosion of mine bombs in real world. Accordingly, the ideas and philosophy of WCA are inspired from water cycle process in the nature and how rivers and streams flow to the sea in the real world. The efficiency of the proposed optimizers was evaluated using numerous well-known unconstrained and constrained benchmark functions which have been widely used in literature. Optimization of several truss structures (2D and 3D) with discrete variables were carried out using the proposed methods and the results and computational performances were compared with several well-known metaheuristic algorithms. The obtained optimization results shows that the proposed new metaheuristic algorithms are capable of offering faster convergence rate in addition to offering better optimal solutions compared to other optimizers. Furthermore, a comparative study was carried out to show the effectiveness of the proposed algorithms over other well-known methods in terms of computational time (speed) and function values. As an illustration of statistical optimization results, the MBA and WCA offer minimum weight of 27,532.95 and 29,304.76, respectively, for the complex 200-bar truss in less number of function evaluations (computational time) compared with other optimizers in the literature.

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