Development of A New Multi-Criteria Optimization Method for Engineering Design Problems

Abstract

In this study, we developed a new multiple criteria optimization method in the context of engineering design. The design of experiment (DoE) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods are combined to identify an objective function of the selected problem by fitting a polynomial to the experimental data in a multiple linear regression analysis. Then, the regression function is incorporated into a mathematical model with the criteria constraints to determine an optimal criteria set. The proposed method can be used to compare the functionality and results provided by different scenario analyses of a building design optimization problem, which represent design solutions. We applied the DoE-TOPSIS model to solve different multi-criteria design optimization problems using two examples from the literature and obtained satisfactory results. In the examples, the results obtained using the combined DoE-TOPSIS model are almost in agreement with those derived from conventional multi-criteria design optimization methods, which demonstrates the simplicity, usability, and flexibility of the proposed method in solving engineering design problems.