Towards optimal ship design and valuable knowledge discovery under uncertain conditions

Ship design is a complex engineering activity which requires a multidisciplinary consideration in arriving at design objectives and constraints. An optimal design of such problems require a multi-objective optimization method that is capable of finding multiple trade-off solutions, not only to choose a preferred solution for implementation, but also to have a deeper understanding of the interactions among design variables. In this paper, we consider two ship design models involving uncertainties in design variables, and demonstrate the usefulness of an evolutionary multiobjective optimization (EMO) method and subsequent data analysis procedures in arriving at valuable design principles that enhance the knowledge of a designer. The study is pedagogical yet provide key insights of ship design issues and importantly outlines the systematic procedure for applying the technology to other more complex design problems.

[1]  Jian-Bo Yang,et al.  Multiple Criteria Decision Support in Engineering Design , 1998 .

[2]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[3]  Kay Chen Tan,et al.  Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms , 2007, Evolutionary Computation in Dynamic and Uncertain Environments.

[4]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[5]  Pratyush Sen,et al.  A Multiple Criteria Genetic Algorithm for Containership Loading , 1997, ICGA.

[6]  Kalyanmoy Deb,et al.  Searching for Robust Pareto-Optimal Solutions in Multi-objective Optimization , 2005, EMO.

[7]  Morgan C. Parker,et al.  A Contextual Multipartite Network Approach to Comprehending the Structure of Naval Design. , 2014 .

[8]  Li Xuebin.  Multiobjective Optimization and Multiattribute Decision Making Study of Ship's Principal Parameters in Conceptual Design , 2009 .

[9]  Kalyanmoy Deb,et al.  Higher-level innovization: A case study from Friction Stir Welding process optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[10]  Kalyanmoy Deb,et al.  Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique , 2011 .

[11]  Kalyanmoy Deb,et al.  Reliability-Based Optimization Using Evolutionary Algorithms , 2009, IEEE Transactions on Evolutionary Computation.

[12]  Gary B. Lamont,et al.  Applications Of Multi-Objective Evolutionary Algorithms , 2004 .

[13]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[14]  Shari E. Hannapel,et al.  Development of Multidisciplinary Design Optimization Algorithms for Ship Design Under Uncertainty. , 2012 .

[15]  Kalyanmoy Deb,et al.  On finding multiple Pareto-optimal solutions using classical and evolutionary generating methods , 2007, Eur. J. Oper. Res..

[16]  Yacov Y. Haimes,et al.  Multiobjective Decision Making: Theory and Methodology , 1983 .

[17]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[18]  Kalyanmoy Deb,et al.  Automated discovery of vital knowledge from Pareto-optimal solutions: First results from engineering design , 2010, IEEE Congress on Evolutionary Computation.

[19]  Tong Heng Lee,et al.  Multiobjective Evolutionary Algorithms and Applications , 2005, Advanced Information and Knowledge Processing.

[20]  Kalyanmoy Deb,et al.  Simulated Binary Crossover for Continuous Search Space , 1995, Complex Syst..

[21]  Kaushik Sinha,et al.  Reliability-based multiobjective optimization for automotive crashworthiness and occupant safety , 2007 .

[22]  Kalyanmoy Deb,et al.  An evolutionary algorithm based approach to design optimization using evidence theory , 2013 .

[23]  Kalyanmoy Deb,et al.  Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms , 2010, SEAL.

[24]  Aravind Srinivasan,et al.  Innovization: innovating design principles through optimization , 2006, GECCO.