Tabu search method with random moves for globally optimal design
Nanfang Hu · International Journal for Numerical Methods in Engineering · 1992
Abstract Optimum engineering design problems are usually formulated as non‐convex optimization problems of continuous variables. Because of the absence of convexity structure, they can have multiple minima, and global optimization becomes difficult. Traditional methods of optimization, such as penalty methods, can often be trapped at a local optimum. The tabu search method with random moves to solve approximately these problems is introduced. Its reliability and efficiency are examined with the help of standard test functions. By the analysis of the implementations, it is seen that this method is easy to use, and no derivative information is necessary. It outperforms the random search method and composite genetic algorithm. In particular, it is applied to minimum weight design examples of a three‐bar truss, coil springs, a Z‐section and a channel section. For the channel section, the optimal design using the tabu search method with random moves saved 26.14 per cent over the weight of the SUMT method.