考虑混合约束的柔顺机构拓扑优化设计

为了满足制造工艺和静强度要求,提出一种综合考虑最小尺寸控制和应力约束的柔顺机构混合约束拓扑优化设计方法。采用改进的固体各向同性材料插值模型描述材料分布,利用多相映射方法同时控制实相和空相材料结构的最小尺寸,采用最大近似函数P范数求解机构的最大应力,以机构的输出位移最大化作为目标函数,综合考虑最小特征尺寸控制和应力约束建立柔顺机构混合约束拓扑优化数学模型,利用移动渐近算法求解柔顺机构混合约束拓扑优化问题。数值算例结果表明,混合约束拓扑优化获得的柔顺机构能够同时满足最小尺寸制造约束和静强度要求,机构的von Mises等效应力分布更加均匀。     

Scheduling on uniform parallel machines with periodic unavailability constraints

Scheduling problems under unavailability constraints has become a popular research topic in the last few years. Despite it’s important application in the real world, the uniform parallel machine scheduling problem was the least studied due to its complexity. In this paper, we investigated the uniform parallel machine scheduling problem under deterministic availability constraints. Each machine is subject to one unavailability period. Different versions of the problem regarding the type of jobs (identical and non-identical) and the performance measures (the total completion times and the makespan) were studied. For the case of identical jobs and for both performance measures, we developed linear programming models and optimal algorithms to provide a solution to the problem. For the case of non-identical jobs, we proved that the problem is NP-hard and propose a quadratic program. Because, this later cannot solve problems with very large number of jobs and machines, a heuristic was developed to find near optimal solutions to the problem especially with very large number of jobs and machines. The computational results showed that the heuristic’s performance is very high regardless the dimensions of problem instances.     

计及输电约束的区域双边电力市场LSFE分析

建立了一个能考虑输电网络约束的区域双边电力市场线性供应函数均衡(LSFE)模型，并分析了在传输线路发生不同阻塞情形时，有套利和无套利不同的假设对发电商市场力、市场平均电价和网络所有者的不同影响。采用基于非线性互补方法的改进的 Levenberg-Marquardt 算法来求解均衡解。30节点的 IEEE 测试系统计算结果表明，套利者的出现可以起到降低市场电价、限制发电商市场力的作用，同时有利于整个市场社会福利和消费者利益的提升。     

Constraint partitioning in penalty formulations for solving temporal planning problems

In this paper, we study the partitioning of constraints in temporal planning problems formulated as mixed-integer nonlinear programming (MINLP) problems. Constraint partitioning is attractive because it leads to much easier subproblems, where each is a significant relaxation of the original problem. Moreover, each subproblem is very similar to the original problem and can be solved by any existing solver with little or no modification. Constraint partitioning, however, introduces global constraints that may be violated when subproblems are evaluated independently. To reduce the overhead in resolving such global constraints, we develop in this paper new conditions and algorithms for limiting the search space to be backtracked in each subproblem. Using a penalty formulation of a MINLP where the constraint functions of the MINLP are transformed into non-negative functions, we present a necessary and sufficient extended saddle-point condition (ESPC) for constrained local minimization. When the penalties are larger than some thresholds, our theory shows a one-to-one correspondence between a constrained local minimum of the MINLP and an extended saddle point of the penalty function. Hence, one way to find a constrained local minimum is to increase gradually the penalties of those violated constraints and to look for a local minimum of the penalty function using any existing algorithm until a solution to the constrained model is found. Next, we extend the ESPC to constraint-partitioned MINLPs and propose a partition-and-resolve strategy for resolving violated global constraints across subproblems. Using the discrete-space ASPEN and the mixed-space MIPS planners to solve subproblems, we show significant improvements on some planning benchmarks, both in terms of the quality of the plans generated and the execution times to find them.     

A Newton-like method for solving rank constrained linear matrix inequalities

This paper presents a Newton-like algorithm for solving systems of rank constrained linear matrix inequalities. Though local quadratic convergence of the algorithm is not a priori guaranteed or observed in all cases, numerical experiments, including application to an output feedback stabilization problem, show the effectiveness of the algorithm.     

Periodic and transient switched server schedules for FMS

Hybrid dynamical approach is an effective way of solving FMS scheduling problems. In this paper the mathematical model and processes determination are shortly reviewed. New results are outlined for the determination of time periods of periodic motions for simple (two part types) problems and for complex (multi-part types, multi-machine groups) cases, too. Having the time periods, all the significant planning parameters can be easily determined. As a consequence of the above, the idea of periodic and transient schedules is introduced. A planning procedure is developed. Based on the new prospects obtained, an important development of the mathematical model is proposed. This is to expand the mathematical model with buffer capacities constraints. These new constraints determine the final results of planning. Using a manipulation of set-up times (regularizibility) a future improvement of the processes can be realized. All this leads to a very simple, real-time scheduling of FMS.     

基于生命周期模型的海洋元数据研究及应用

分析在海洋领域元数据应用情况和标准化现状,提出基于生命周期的海洋元数据标准的设计框架;并在框架内针对海洋数据过程特点提出基于生命周期的海洋元数据管理模型;在海洋数据综合管理平台中基于生命周期的海洋元数据进行设计。     

TOC在逆向物流回收配送整合决策模型中的应用研究

将约束理论应用于逆向物流中，利用约束理论的相关评价指标，以有效产出作为决策目标，构建了一个逆向物流回收配送整合决策模型，对逆向物流系统进行整体优化，并且以一个回收处理橡胶废弃物的企业作为算例，通过对比基于TOC的决策模型和基于成本最小化的传统决策模型的运算结果，说明了约束理论在解决这类问题中的优越性．将约束理论的作业衡量标准应用于回收配送的过程，加强对逆向物流的管理，能够使逆向物流从整体上发挥最大效益．     

基于TOC的业务外包决策模型研究

建立了业务外包决策问题的数学模型,阐述了标准约束理论下业务外包决策过程,指出了多瓶颈情形下标准TOC方法的不足,提出了集成作业成本法的改进模型,较好地解决了多瓶颈问题,分析了新模型制定短期决策和长期决策的侧重点.实践证明,新模型制定的业务外包决策比标准TOC方法模型更合理有效,企业获取的利润更大.     

The Nonlocal Newton Method for Convex Optimization Problems and Monotone Variational Inequalities

The nonlocal Newton method is developed for nonlinear problems of conditional convex optimization and monotone variational inequalities in a finite-dimensional space. The Newton direction vector is calculated from a solution of a linear-approximating variational inequality. A new penalty function is proposed to define a step length.