Numerous real-world problems relating to ship design are characterized by many alternatives as well as multiple conflicting objectives. Ship design is a complex endeavor requiring the successful coordination of many different disciplines, both technical and nontechnical. Conceptual design is the least defined stage of the ship design process and seeks to define the basic payloads and ship size characteristics. A hybrid approach for multiobjective optimization study of ship's principal parameters in conceptual design is proposed in the present analysis. In the first stage, a multiple objective genetic algorithm (MOGA) is employed to approximate the set of Pareto solution through an evolutionary optimization process. In the subsequent stage, a multiattribute decision making (MADM) approach is adopted to rank these solutions from best to worst and to determine the best solution in a deterministic environment with a single decision maker. A bulk carrier example, with 6 parameters, 3 criteria, and 14 constraints is conducted to illustrate the analysis process in present study. Pareto frontiers are obtained, and the ranking of the Pareto solution set is based on entropy weight and TOPSIS method. The ideal solution is compared with those from classic multiobjective methods.