1. A computer-implemented method of obtaining a set of diversified Pareto optimal solutions a multi-objective evolutionary algorithm (MOEA) based engineering design optimization of a product, said method comprising: receiving, in a computer system, a description of a product to be optimized; conducting a plurality of MOEA based engineering design optimizations of the product independently, the engineering design optimizations being configured to use a set of common design variables and a set of common design objective functions, wherein each of the engineering design optimizations differs from others in initial generation's design alternatives and evolution schemes consisted of Nondominated Sorting Genetic Algorithm (NSGA-II) and strength Pareto evolutionary algorithm (SPEA); obtaining a combined set of Pareto optimal solutions at one or more predefined checkpoints by combining Pareto optimal solutions resulted from said each of the engineering optimizations; and designating the combined set of Pareto optimal solutions as global Pareto optimal solutions when any or all of engineering design optimizations have converged based on spread and uniformity measurements, wherein the global Pareto optimal solutions are stored in a storage device and graphically displayed in a monitor upon user's instruction.