基于映射理论下的决策评判模型

按照映射理论,通过建立评价指标标准值与评价指标标准值顺序数之间的函数,将非等长度区间映射成长度为1的等长区间,提出了一种求解决策评判的新模型,解决了不同标度下的评价因子、评价类别的决策评判问题,纠正了可拓理论关联函数基本公式的错误,简化了可变模糊集模型中的M矩阵和B矩阵,进而统一了可拓评价和可变模糊集理论在决策评判中的一致性,并实例验证了模型的优越性和正确性,对决策评判问题具有重要的应用拓广参考价值.     

Design of a motorcycle frame using neuroacceleration strategies in MOEAs

Designing a low-budget lightweight motorcycle frame with superior dynamic and mechanical properties is a complex engineering problem. This complexity is due in part to the presence of multiple design objectives—mass, structural stress and rigidity—, the high computational cost of the finite element (FE) simulations used to evaluate the objectives, and the nature of the design variables in the frame’s geometry (discrete and continuous). Therefore, this paper presents a neuroacceleration strategy for multiobjective evolutionary algorithms (MOEAs) based on the combined use of real (FE simulations) and approximate fitness function evaluations. The proposed approach accelerates convergence to the Pareto optimal front (POF) comprised of nondominated frame designs. The proposed MOEA uses a mixed genotype to encode discrete and continuous design variables, and a set of genetic operators applied according to the type of variable. The results show that the proposed neuro-accelerated MOEAs, NN-NSGA II and NN-MicroGA, improve upon the performance of their original counterparts, NSGA II and MicroGA. Thus, this neuroacceleration strategy is shown to be effective and probably applicable to other FE-based engineering design problems.     

A Semi-Infinite Programming Model In Data Envelopment Analysis

We consider a model for data envelopment analysis with infinitely many decision-making units. The determination of the relative efficiency of a given decision-making unit amounts to the solution of a semi-infinite optimization problem. We show that a decision-making unit of maximal relative efficiency exists and that it is 100% efficient. Moreover, this decision-making unit can be found by calculating a zero of the semi-infinite constraint function. For the latter task we propose a bi-level algorithm. We apply this algorithm to a problem from chemical engineering and present numerical results