An evaluation method of the functional diversity and structural similarity among products, and its application to computer aided design system

近年来，要求制造企业高效、经济地生产多种、小批量的制成品。本研究的目的是提出一种新的产品设计方法论，该方法论考虑了产品之间的功能多样性和结构相似性。首先，将产品的设计过程描述为一个适当的优化问题。然后，采用遗传算法、变邻域搜索等元启发式方法寻找优化问题的各种最优解。为了证明我们提出的设计技术的有效性，我们研究了以下实际问题1。模块布局问题为了解决在超大规模集成电路设计中具有特殊意义的模块布局问题的多个最优解，提出了一种基于Imanishi进化理论的遗传算法。还采用了一种新的度量函数来评估种群中包含的解或个体的多样性。装配机器人控制为了从多目标资源划分问题的整个帕累托前沿抽样各种解决方案，引入了两个解决方案之间的功能距离和结构距离。然后，将Imanishian遗传算法应用于该问题。电子器件的优化设计一个三叉指换能型声表面波滤波器的结构设计被描述为一个组合优化问题。然后，提出了一种新的基于k次邻域的局部搜索方法，并将其应用于该问题。

In recent years, manufactures are required to product many kinds and small numbers of manufactured goods effectively and economically. The purpose of this research is to present a new design methodology of products that considers functional diversity and structural similarity among them. First of all, the procedure of designing products is formulated as an appropriate optimization problem. Then, for finding various optimal solutions of the optimization problem, a meta-heuristic method, such as genetic algorithm and variable neighborhood search, is employed. In order to demonstrate the usefulness of our proposed design technique, we have studied the following practical problems.1. Module Placement ProblemIn order to find the plural number of optimal solutions for the module placement problem, which is of particular significance in the design of VLSI, a new Genetic Algorithm (GA) based on the Imanishi's evolutionary theory is proposed. A new metric function is also employed to evaluate the diversity of solutions, or individuals, included in the population.2. Assembly Robot ControlFor sampling various solutions from the entire Pareto front of the multiobjective resource division problem, functional and structural distances between two solutions are introduced. Then, the Imanishian GA is applied to the problem.3. Optimal Design of Electronic DeviceThe structural design of a three-IDT type Surface Acoustic Wave filter is formulated as a combinatorial optimization problem. Then, a new local search method based on the k-degree-neighborhood is proposed and applied to the problem.