A Methodology Using Partial Swarm Optimization and Kriging to Ship Multidisciplinary Design Optimization

Abstract

Ship optimization design is a complex multidisciplinary process due to determining ship configuration variables that satisfy a set of mission requirements. In this paper A Monte Carlo method (MCM) is employed to explore the design space and to sample data for covering the design space. Particularly in ship multidisciplinary design optimization, we investigate the use of kriging sampling methods for constructing global approximations and fit model to facilitate multidisciplinary design optimization (MDO). In this search (MDO) are used to computational expense and organizational complexity, Partial Swarm Optimization (PSO) adopt as a feasible alternative to the existing sizing and optimization methods and to illustrate the appropriate design result in approach through (MDO) process, the objective of this search to minimum ship running cost which it subjected to constraints in performance, geometric parameters, power of population and voyage. Finally, the validity of the proposed methodology is proven by a case study of a bulk carrier.