Tabu search for multiple-criteria manufacturing cell design

Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design.     

基于禁忌搜索算法的电磁场逆问题鲁棒优化设计

为了综合分析优化解的性能,讨论了参数不确定条件下电磁场逆问题的鲁棒优化性。分析了鲁棒优化设计方法,研究了鲁棒期望适值函数关键参数的估计方法。以寻求鲁棒最优解为目标,应用改进的禁忌算法,基于鲁棒性能期望适值函数,求解了典型数学问题和工程设计问题。通过计算比较叠加扰动最优解条件下的目标函数值偏差,其结果表明,该研究算法能够快速有效地搜索到鲁棒最优解。     

Fuzzy rule base design using tabu search algorithm for nonlinear system modeling

This paper presents an approach to fuzzy rule base design using tabu search algorithm (TSA) for nonlinear system modeling. TSA is used to evolve the structure and the parameter of fuzzy rule base. The use of the TSA, in conjunction with a systematic neighbourhood structure for the determination of fuzzy rule base parameters, leads to a significant improvement in the performance of the model. To demonstrate the effectiveness of the presented method, several numerical examples given in the literature are examined. The results obtained by means of the identified fuzzy rule bases are compared with those belonging to other modeling approaches in the literature. The simulation results indicate that the method based on the use of a TSA performs an important and very effective modeling procedure in fuzzy rule base design in the modeling of the nonlinear or complex systems.     

面向变批量生产的制造单元构建方法

为实现变批量生产特征下制造资源的优化利用,提出一种有效的制造单元构建方法。在构建制造单元框架模型中,提出应先对现有单元布局可用性进行分析的策略,并考虑现有单元布局对变批量生产的一种适应性。以单元布局的可用性和物料搬运成本最小化为目标,构建了目标函数和约束条件模型,集成考虑了设备聚类和单元布局问题,同时利用改进粒子群算法对问题进行求解,并对粒子进行二维实数编码,解决了粒子群算法求解离散空间优化问题。通过一个实例验证了所提方法的有效性。     

云制造环境中面向设计知识资源序列化组合的量子和声搜索算法

针对云制造环境下中小企业设计知识散乱无序、创新能力薄弱的现状,为将设计知识组合成有序的知识资源序列,提出知识资源的服务能力评估模型和知识资源序列化组合的数学模型,并设计了求解该模型的量子和声搜索算法。该算法通过引入量子化编码及量子门变换,提高了全局搜索能力。以模具中小企业设计知识资源组合优化问题为例,根据数学模型,用该算法求解出了成本与质量综合约束下的最优设计知识资源序列化组合。