New Branch-and-Cut Algorithm for Bilevel Linear Programming

Linear mixed 0–1 integer programming problems may be reformulated as equivalent continuous bilevel linear programming (BLP) problems. We exploit these equivalences to transpose the concept of mixed 0–1 Gomory cuts to BLP. The first phase of our new algorithm generates Gomory-like cuts. The second phase consists of a branch-and-bound procedure to ensure finite termination with a global optimal solution. Different features of the algorithm, in particular, the cut selection and branching criteria are studied in details. We propose also a set of algorithmic tests and procedures to improve the method. Finally, we illustrate the performance through numerical experiments. Our algorithm outperforms pure branch-and-bound when tested on a series of randomly generated problems. Work of the authors was partially supported by FCAR, MITACS and NSERC grants.     

Discrete global descent method for discrete global optimization and nonlinear integer programming

A novel method, entitled the discrete global descent method, is developed in this paper to solve discrete global optimization problems and nonlinear integer programming problems. This method moves from one discrete minimizer of the objective function f to another better one at each iteration with the help of an auxiliary function, entitled the discrete global descent function. The discrete global descent function guarantees that its discrete minimizers coincide with the better discrete minimizers of f under some standard assumptions. This property also ensures that a better discrete minimizer of f can be found by some classical local search methods. Numerical experiments on several test problems with up to 100 integer variables and up to 1.38 × 10¹⁰⁴ feasible points have demonstrated the applicability and efficiency of the proposed method.     

托卡马克能量约束及自举电流效应的初步考虑

基于Lee等人的离子温度梯度模导致的反常热能输运系数,本文研究了辅助加热托卡马克等离子体的能量约束行为,并对自举电流的效应作了初步考虑。结果表明,计算得到的能量约束时间随等离子体电流I_p和托卡马克大半径R增大而增长,随注入功率P_t、环向场B_t以及等离子体小半径α的增大而缩短。这些结果与Kaye-Goldston的经验约束定标具有相同的趋势。自举电流的存在总是导致能量约束时间的增加,当自举电流与总电流的比值γ较小时,能量约束时间的增加率约为γ/2。此外,自举电流将造成锯齿反转半径的减小。     

Optical current transducer with bulk type Bi12SiO20 faraday sensor for power systems

Two types of optical current transducers (OCTs) have a bulk Faraday sensor inserted into the gap of an iron core and a porcelain insulator with optical fiber. The sensor consists of Bi₁₂SiO₂₀ (BSO) single crystal, a polarizer, and an analyzer. The OCTs satisfied the target performance requirement for fault location and metering and demonstrated maintained performance at some power utilities in Japan and the US. We have developed a fault location system that immediately detects the fault current with the OCTs, there by locating the fault section. The OCT can easily replace the existing support insulators for the disconnecting switch without any modifications to structure height or bus-bar. For metering requiring 0.3% class accuracy, use of a BSO with right optical rotatory power combined with BSO with left optical rotatory power results in a Faraday sensor with improved temperature characteristics. The OCT demonstrated 0.3% class accuracy for metering described in the current transformer Specifications of IEEE C57–13, 1993.     

多气隙电阻板室抗辐照性能研究

给出了为RHIC-STAR飞行时间探测器设计的多气隙电阻板室(MRPC)的辐照实验结果. 实验采用100mCi⁶⁰Co γ源, 采用不同的剂量率对MRPC进行辐照. 一个室在大剂量率2.87×10^－2Gy/h下辐照了24h后, 其性能如噪声计数率, 暗电流等均大大退化. 另一个室在相对低剂量率5.31×10^－4Gy/h下辐照了530h, 其性能没有见到任何变坏. 实验的目的是为了了解这种探测器在几年的运行中经过大剂量的辐照后的性能变化情况.     

交流源作用下介观RLC电路系统量子态随时间的演化

根据量子不变量理论，同时考虑介观电容器极板间电子波函数的耦合作用和电路的耗散,研究介观RLC电路系统在交流电流源作用下动力学的演化过程，并且得到描述系统量子态随时间的演化算符.进一步的分析结果表明，介观RLC电路系统的波函数将由任意的初态演化到一般的压缩态. 关键词： 介观RLC电路 交变电源 不变量理论 时间演化算符     

s波超导体绝缘层dx2-y2波超导体结的直流Josephson电流

在s波超导体绝缘层dx2-y2波超导体结(sId)中,考虑到结界面粗糙散射,运用BogoliubovdeGennes(BdG)方程和FurusakiTsukada(FT)电流公式,计算超导结中的准粒子传输系数和直流Josephson电流.结果表明:sId超导结的直流Josephson电流随温度以及结两侧的相位差变化的关系曲线强烈地依赖于d波超导体的晶轴方位;结界面的粗糙散射对Josephson电流有抑制作用 关键词： s/I/d超导结 dx2-y2波超导体 直流Josephson电流     

Computing Aviation Sparing Policies: Solving a Large Nonlinear Integer Program

Deployed US Navy aircraft carriers must stock a large number of spare parts to support the various types of aircraft embarked on the ship. The sparing policy determines the spares that will be stocked on the ship to keep the embarked aircraft ready to fly. Given a fleet of ten or more aircraft carriers and a cost of approximately 50 million dollars per carrier plus the cost of spares maintained in warehouses in the United States, the sparing problem constitutes a significant portion of the Navy’s resources. The objective of this work is to find a minimum-cost sparing policy that meets the readiness requirements of the embarked aircraft. This is a very large, nonlinear, integer optimization problem. The cost function is piecewise linear and convex while the constraint mapping is highly nonlinear. The distinguishing characteristics of this problem from an optimization viewpoint are that a large number of decision variables are required to be integer and that the nonlinear constraint functions are essentially “black box” functions; that is, they are very difficult (and expensive) to evaluate and their derivatives are not available. Moreover, they are not convex. Integer programming problems with a large number of variables are difficult to solve in general and most successful approaches to solving nonlinear integer problems have involved linear approximation and relaxation techniques that, because of the complexity of the constraint functions, are inappropriate for attacking this problem. We instead employ a pattern search method to each iteration of an interior point-type algorithm to solve the relaxed version of the problem. From the solution found by the pattern search on each interior point iteration, we begin another pattern search on the integer lattice to find a good integer solution. The best integer solution found across all interations is returned as the optimal solution. The pattern searches are distributed across a local area network of non-dedicated, heterogeneous computers in an office environment, thus, drastically reducing the time required to find the solution.     

Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing

We define events so as to reduce the number of events and decision variables needed for modeling batch-scheduling problems such as described in [15]. We propose a new MILP formulation based on this concept, defining non-uniform time periods as needed and decision variables that are not time-indexed. It can handle complicated multi-product/multi-stage machine processes, with production lines merging and diverging, and with minimum and maximum batch sizes. We compare it with earlier models and show that it can solve problems with small to medium demands relative to batch sizes in reasonable computer times.