Solving Engineering Optimization Problems by a Deterministic Global Optimization Approach

Engineering optimization problems are normally formulated as nonlinear programming problems and adopted in a lot of research to show the effectiveness of new optimization algorithms. These problems are usually solved through deterministic or heuristic methods. Because non-convex functions exist in most engineering optimization problems that possess multiple local optima, the heuristic methods cannot guarantee the global optimality of the obtained solution. Although many deterministic approaches have been developed for treating non-convex engineering optimization problems, these methods use too many extra binary variables and constraints in reformulating the problems. Therefore, this study applies an efficient deterministic approach for solving the engineering optimization problem to find a global optimum. The deterministic global approach transforms a non-convex program into a convex program by convexification strategies and piecewise linearization techniques and is thus guaranteed to reach a global optimum. Some practical engineering design problems are presented and solved to demonstrate that this study is able to obtain a better solution than other methods.