A sophisticated GA/PSO-hybrid algorithm for application to real-world optimization problems was proposed. The configurations of the two consisting methods, GA and PSO, were investigated to enhance the diversity of the former and the fast convergence of the latter simultaneously. The new hybrid algorithm was applied to two test function problems, and the results indicated that the search ability was improved by suitable tuning of the configurations. In addition, the new hybrid algorithm showed robust search ability regardless of the selection of the initial population. The new hybrid algorithm was also applied to a diesel engine combustion chamber design problem. The obtained non-dominated solutions have a variety in their configurations. Several solutions that dominate the baseline configuration were successfully found within a few generations, and the trade-off relation between soot reduction and diffusion combustion period was also determined. In addition, useful design information was obtained by investigating the optimization results; the length from the center of the combustion chamber to the lip is the control design variable of trade-off between the soot reduction and diffusion combustion period, and the large width of the center of the combustion chamber improves soot emission and diffusion combustion period at the same time.