Two-storage inventory model with lot-size dependent fuzzy lead-time under possibility constraints via genetic algorithm

Multi-item inventory models with stock dependent demand and two storage facilities are developed in a fuzzy environment where processing time of each unit is fuzzy and the processing time of a lot is correlated with its size. These are order-quantity reorder-point models with back-ordering if required. Here possibility and crisp constraints on investment and capacity of the small storehouse respectively are considered. The models are formulated as fuzzy chance constrained programming problem and is solved via generalized reduced gradient (GRG) technique when crisp equivalent of the constraints are available. A genetic algorithm (GA) is developed based on fuzzy simulation and entropy where region of search space gradually decreases to a small neighborhood of the optima and it is used to solve the models whenever the equivalent crisp form of the constraint is not available. The models are illustrated with some numerical examples and some sensitivity analyses have been done. For some particular cases results observed via GRG and GA are compared.     

Algorithms for Unconstrained Optimization Problems via Control Theory

Existing algorithms for solving unconstrained optimization problems are generally only optimal in the short term. It is desirable to have algorithms which are long-term optimal. To achieve this, the problem of computing the minimum point of an unconstrained function is formulated as a sequence of optimal control problems. Some qualitative results are obtained from the optimal control analysis. These qualitative results are then used to construct a theoretical iterative method and a new continuous-time method for computing the minimum point of a nonlinear unconstrained function. New iterative algorithms which approximate the theoretical iterative method and the proposed continuous-time method are then established. For convergence analysis, it is useful to note that the numerical solution of an unconstrained optimization problem is none other than an inverse Lyapunov function problem. Convergence conditions for the proposed continuous-time method and iterative algorithms are established by using the Lyapunov function theorem.     

Learning about multiplication by comparing algorithms: “One times one,but actually they are ten times ten”

Multiplication algorithms in primary school are still frequently introduced with little attention to meaning. We present a case study focusing on a third grade class that engaged in comparing two algorithms and discussing “why they both work”. The objectives of the didactical intervention were to foster students' development of mathematical meanings concerning multiplication algorithms, and their development of an attitude to judge and compare the value and efficiency of different algorithms. Underlying hypotheses were that it is possible to promote the simultaneous unfolding of the semiotic potential of two algorithms, considered as cultural artifacts, with respect to the objectives of the didactical intervention, and to establish a fruitful synergy between the two algorithms. As results, this study sheds light onto the new theoretical construct of “bridging sign”, illuminating students’ meaning-making processes involving more than one artifact; and it provides important insight into the actual unfolding of the hypothesized potential of the algorithms.     

地质灾害图形图象分析系统在天津地面沉降分析中的应用

地质灾害的分布和发生发展过程具有空间特性, 其影响因素具有自身的特点和复杂性。作者开发的地质灾害图象分析系统(GHMIAS)是以典型地质灾害为主要对象、以空间信息管理和分析为主要功能的应用性地理信息系统, 该系统有独特的空间分析模型扩充, 融矢量、栅格和Windows图形用户对象为一体, 支持多种数据格式相互转换, 具有丰富的制图功能和高质量的制图输出, 可以快速生成灾害专题图件。     

SPATIAL AND SEASONAL DISTRIBUTIONS OF ATMOSPHERIC CARBONACEOUS AEROSOLS IN PEARL RIVER DELTA REGION, CHINA

Concentrations and spatial distributions of organic carbon (OC) and elemental carbon (EC) in atmospheric particles were measured at 8 sites in four cities (Hong Kong, Guangzhou, Shenzhen and Zhuhai) of Pearl River Delta Region (PRDR), China during 2001 winter period and 2002 summer period. PM2.5 (particie diameter smaller than 2.5 um) and PM10 (particie diameter smaller than 10 um) samples were collected on pre-fired quartz filters with mini-volume samplers and analyzed using thermal optical reflectance (TOR) method. The average PM2.5and PM10 Ievel were 60.1 and 93.1 μg·m-3, respectively, with PM2.5 constituting 65.3% of the PM10 mass. The average OC and EC concentrations in PM2.5 were 12.0 and 5.1 μg·m-3, respectively, while those in PM10 were 16.0 and 6.5 μg·m-3, respectively. The carbo-naceous aerosol accounted for 37.2% of the PM2.5 and 32.8% of the PM10. The highest concentrations of OC and EC were observed at Guangzhou city in both vvinter and summer seasons. The average OC/EC ratios were 2.     

A hybrid trust region algorithm for unconstrained optimization

This paper presents a hybrid trust region algorithm for unconstrained optimization problems. It can be regarded as a combination of ODE-based methods, line search and trust region techniques. A feature of the proposed method is that at each iteration, a system of linear equations is solved only once to obtain a trial step. Further, when the trial step is not accepted, the method performs an inexact line search along it instead of resolving a new linear system. Under reasonable assumptions, the algorithm is proven to be globally and superlinearly convergent. Numerical results are also reported that show the efficiency of this proposed method.     

等式约束优化非单调信赖域算法

设计了一个新的求解等式约束优化问题的非单调信赖域算法.该算法不需要罚函数也无需滤子.在每次迭代过程中只需求解满足下降条件的拟法向步及切向步.新算法产生的迭代步比滤子方法更易接受,计算量比单调算法小.在一般条件下,算法具有全局收敛性.     

A matheuristic approach with nonlinear subproblems for large-scale packing of ellipsoids

The problem of packing ellipsoids in the three-dimensional space is considered in the present work. The proposed approach combines heuristic techniques with the resolution of recently introduced nonlinear programming models in order to construct solutions with a large number of ellipsoids. The introduced approach is able to pack identical and non-identical ellipsoids within a variety of containers. Moreover, it allows the inclusion of additional positioning constraints. This fact makes the proposed approach suitable for constructing large-scale solutions with specific positioning constraints in which density may not be the main issue. Numerical experiments illustrate that the introduced approach delivers good quality solutions with a computational cost that scales linearly with the number of ellipsoids; and solutions with more than a million ellipsoids are exhibited.