In this research, a methodology is presented to optimize the life performance of mechanical systems using multiple objective evolutionary algorithm. Conflicting objectives are encountered (e.g. low costs and longer service life) here along with significant number of constraints (e.g. technological limitations, weight and volume). To solve the design optimization problems, the objective function is weighted with a combination of the targets. The evolutionary algorithm (i.e. GA) is applied for minimization of the system failure rates, reliability allocation optimization. The failure rates are optimally estimated for the system?s critical components. Reliability allocation technique is utilized to determine the optimum reliability of the constituent components with higher failure rates. The reliability targets are determined for the components through the minimized failure rates. The methodology is demonstrated through a case study, on a centrifugal pump. The pump design requires consideration of several targets and requirements with different weight factors for satisfaction (e.g., availability, capability, efficiency and weight) along the pump life. Analytical Hierarchy Process (AHP) is utilized to determine the weights of the objectives. As a result of this research, the equipment design is improved, costly over-designs options are prevented and development tests are optimized.