Solving advanced multi-objective robust designs by means of multiple objective evolutionary algorithms (MOEA): A reliability application

This paper extends the approach proposed by the second author in [Rocco et al. Robust design using a hybrid-cellular-evolutionary and interval-arithmetic approach: a reliability application. In: Tarantola S, Saltelli A, editors. SAMO 2001: Methodological advances and useful applications of sensitivity analysis. Reliab Eng Syst Saf 2003;79(2):149-59 [special issue]] to obtain a robust system design. The approach based on the use of evolutionary algorithms and interval arithmetic finds the maximum-volume inner box (MIB) or the maximal ranges of variation for each variable that preserve pre-specified design/performance requirements. The original single-objective formulation considers the definition of a MIB around a specified centroid (case 1), or around an unspecified centroid (case 2). In this paper, both cases were successfully modified and solved as multiple-objective (MO) problems, showing the advantages of MO formulations in a design-selection decision framework. Special attention is devoted to the unspecified centre MO problem where the computational efficiency could be a critical issue. In that sense, a new procedure based on the “percentage representation” is proposed. This approach reduces drastically the computational burden, extending the possibilities of use of robust design.     

Heuristic factory planning algorithm for advanced planning and scheduling

This study focuses on solving the factory planning (FP) problem for product structures with multiple final products. In situations in which the capacity of the work center is limited and multiple job stages are sequentially dependent, the algorithm proposed in this study is able to plan all the jobs, while minimizing delay time, cycle time, and advance time. Though mixed integer programming (MIP) is a popular way to solve supply chain factory planning problems, the MIP model becomes insolvable for complex FP problems, due to the time and computer resources required. For this reason, this study proposes a heuristic algorithm, called the heuristic factory planning algorithm (HFPA), to solve the supply chain factory planning problem efficiently and effectively. HFPA first identifies the bottleneck work center and sorts the work centers according to workload, placing the work center with the heaviest workload ahead of the others. HFPA then groups and sorts jobs according to various criteria, for example, dependency on the bottleneck work center, the workload at the bottleneck work center, and the due date. HFPA plans jobs individually in three iterations. First, it plans jobs without preempting, advancing, and/or delaying. Jobs that cannot be scheduled under these conditions are scheduled in the second iteration, which allows preemption. In the final iteration, which allows jobs to be preempted, advanced, and delayed, all the remaining jobs are scheduled. A prototype was constructed and tested to show HFPA's effectiveness and efficiency. This algorithm's power was demonstrated using computational and complexity analysis.     

Implementation of polynomial multi-objective optimization in Mathematica

We describe implementation of main methods for solving polynomial multi-objective optimization problems by means of symbolic processing available in the programming language MATHEMATICA. Symbolic transformations of unevaluated expressions, representing objective functions and constraints, into the corresponding representation of the single-objective constrained problem are especially emphasized. We also describe a function for the verification of Pareto optimality conditions and a function for graphical illustration of Pareto optimal points and given constraint set.     

圆柱螺旋压缩弹簧的多目标模糊优化设计

综合运用模糊数学理论和优化设计方法，建立起了基于模糊综合评判的圆柱螺旋压缩弹簧多目标模糊优化设计的数学模型，对圆柱螺旋压缩弹簧多目标模糊优化设计方法进行了探讨，并给出了设计实例，结果表明，基于模糊综合评判的圆柱螺旋压缩弹簧多目标模糊优化设计，是一种更具有工程实用价值的综合设计方法。     

活塞环非圆轮廓数控仿形系统

介绍一种活塞环非圆轮廓曲线数控仿形技术及系统外界扰动信号的智能决策与模糊控制技术，以一个近似于二次谐波曲线的凸轮作为驱动刀具进给的正弦机构，进给行程通过调整杆杆杜来改变，可以在电机不反转的前提下，实现刀具进给运动，从而大大提高系统的频响，借助调节电机转度，使刀具进行速度与主轴速度保持某种预定关系（与活塞环型号，规格有关）便可加工出不同型号和规格的活塞环零件，采用智能决策方法和模糊控制规则，形成专家     

面向多输出电路的BDD拼接构造

二元判定图(Binary Decision Diagram,BDD)的有效描述将大大提高验证和测试生成效率。作者根据电路结构的特点,以标准门的BDD为基础,从原始输入到输出,通过逐级拼接,极有效地完成电路的BDD构造。另外根据验证和测试的需要,在BDD拼接过程中,提出通过可观值的定义获得有效路径的方法。实验证明,作者提出的方法简单、直观而且有效。     

基于供应链运作参考模型的供应链多目标绩效优化模型

为研究供应商—制造商两级供应链的多目标绩效优化问题,引入供应链运作参考模型的绩效评价体系,给出了供应链成本、资产波动、敏捷性、可靠性、响应性的具体计算方法,构建了供应链的凸二次多目标绩效优化模型,基于扩展的约束算法思想编写程序并调用CPLEX 12优化软件求解该模型,得到供应链的帕累托有效绩效集以及供应商和制造商的生产决策方案。通过案例模拟表明了模型的可解性和应用性。     

油气管道设计的多目标模糊物元局势的决策

运用模糊物元局势决策方法，对油气管道多目标设计方案进行评价、优选，结合实例计算，得到与其他方法相同的效果，结论符合实际。     

Container storage space assignment problem in two terminals with the consideration of yard sharing

Facing the shortage of storage space of container terminal yard, a yard sharing strategy that uses dry port's surplus storage space to ease container congestion is proposed. This novel strategy can address the container storage space assignment problem for inbound containers. The problem is studied based on the storage yard of the combined container terminal and dry port. First, a multiple-objective mixed integer programming model that considers yard sharing strategy with the objectives of minimizing total travel distance, minimizing imbalance in number of containers, maximizing shared storage space of the dry port is formulated to obtain optimal solutions. Second, a non-dominated sorting genetic algorithm II (NSGA-II) is proposed. Next, the performance of the algorithm is verified by a set of instances. Numerical experiments are conducted to elucidate the problem with yard sharing strategy intuitively. Furthermore, the performance of the model in four aspects proclaims the advantages of yard sharing strategy and certifies the comprehensiveness. Finally, sensitivity analysis is conducted by two aspects which are weight coefficient and feasible distance to verify the efficiency of the proposed method.