大型舰船主尺度方案生成及优选

基于多目标混沌差分进化算法(CDEMO)与直觉模糊多属性群决策(IFMAGDM)对大型舰船主尺度方案生成及优选进行了研究.建立了主尺度方案评价指标体系，以客观属性指标为优化目标建立优化模型，采用CDEMO对模型进行求解，生成了Pareto最优方案集.引入IFMAGDM模型对方案进行优选，针对群决策一致性修正问题，引入最大调整程度的概念对迭代算法进行改进，使一致性修正既简便高效又符合专家初始偏好.通过实例研究验证了一致性修正方法具有很高的可靠性，所提出的方案生成及优选方法具有很高的实用性，为大型舰船初步设计提供了一种简便、高效的新方法.

Scheme Generation and Optimal Selection of Principal Dimensions for Large Naval Ships

Scheme generation and optimal selection of principal demensions for large naval ships were studied based on chaotic differntial evlution for multi-objective(CDEMO) and instuitionistic fuzzy multiple attribute group decision making(IFMAGDM). An optimization model was established using objective attribute indexes. The pareto-optimal scheme set was generated using CDEMO. The model of IFMAGDM was introduced for scheme optimal selection. Aimed at the problem of consisency correction, the concept of adjustment of biggest degree was proposed to improve the iterative algorithm, which was efficient and satisfying to the initial preference of experts. The case study indicates that the method of consisency correction is highly reliable and the proposed mothod for scheme generation and optimal selection is highly practical, which offers a novel, simple and efficient avenue for large naval ship preliminary design.