Frequently, optimization cases in engineering and other heavy industries present themselves in a multi-objective setting. Thus, it would greatly aid the decision maker if a series of multiple solutions were at hand prior to selecting the suitable solution. In this work, the weighted sum scalarization approach was used in conjunction with the Differential Evolution (DE) and the improved Hopfield Differential Evolution (Hopf-DE) algorithm. The DE and Hopf-DE approaches were then applied to the cement-bonded sand mould system to construct the approximate Pareto frontier, which was then employed to identify the best solution option. Some analysis was then performed on the computational results produced. Examination of the performance and the quality of the solutions obtained by the DE and Hopf-DE algorithms is presented. In addition, an analysis of the degree of conflict between the two objective functions with respect to the search space was carried out. The findings from this analysis are discussed in this paper. © 2014, © 2013 International Society of Management Science and Engineering Management.