A sufficient descent LS conjugate gradient method for unconstrained optimization problems

In this paper, we make a modification to the Liu-Storey (LS) conjugate gradient method and propose a descent LS method. The method can generate sufficient descent directions for the objective function. This property is independent of the line search used. We prove that the modified LS method is globally convergent with the strong Wolfe line search. The numerical results show that the proposed descent LS method is efficient for the unconstrained problems in the CUTEr library.     

The Möbius function of separable and decomposable permutations

We give a recursive formula for the Möbius function of an interval [σ,π] in the poset of permutations ordered by pattern containment in the case where π is a decomposable permutation, that is, consists of two blocks where the first one contains all the letters 1,2,…,k for some k. This leads to many special cases of more explicit formulas. It also gives rise to a computationally efficient formula for the Möbius function in the case where σ and π are separable permutations. A permutation is separable if it can be generated from the permutation 1 by successive sums and skew sums or, equivalently, if it avoids the patterns 2413 and 3142.We also show that the Möbius function in the poset of separable permutations admits a combinatorial interpretation in terms of normal embeddings among permutations. A consequence of this interpretation is that the Möbius function of an interval [σ,π] of separable permutations is bounded by the number of occurrences of σ as a pattern in π. Another consequence is that for any separable permutation π the Möbius function of (1,π) is either 0, 1 or −1.     

A new method of moving asymptotes for large-scale linearly equality-constrained minimization

A new method of moving asymptotes for large-scale minimization subject to linear equality constraints is discussed.In this method,linear equality constraints are deleted with null space technique and the descending direction is obtained by solving a convex separable subproblem of moving asymptotes in each iteration. New rules for controlling the asymptotes parameters are designed and the global convergence of the method under some reasonable conditions is established and proved.The numerical results show that the new method may be capable of processing some large scale problems.     

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.     

Quantum-inspired space search algorithm (QSSA) for global numerical optimization

This work presents the evolutionary quantum-inspired space search algorithm (QSSA) for solving numerical optimization problems. In the proposed algorithm, the feasible solution space is decomposed into regions in terms of quantum representation. As the search progresses from one generation to the next, the quantum bits evolve gradually to increase the probability of selecting the regions that render good fitness values. Through the inherent probabilistic mechanism, the QSSA initially behaves as a global search algorithm and gradually evolves into a local search algorithm, yielding a good balance between exploration and exploitation. To prevent a premature convergence and to speed up the overall search speed, an overlapping strategy is also proposed. The QSSA is applied to a series of numerical optimization problems. The experiments show that the results obtained by the QSSA are quite competitive compared to those obtained using state-of-the-art IPOP-CMA-ES and QEA.     

A tree search method for the container loading problem with shipment priority

This paper addresses a special kind of container loading problem with shipment priority. We present a tree search method, which is based on a greedy heuristic. In the greedy heuristic, blocks made up of identical items with the same orientation are selected for packing into a container. Five evaluation functions are proposed for block selection, and the different blocks selected by each evaluation function constitute the branches of the search tree. A method of space splitting and merging is also embedded in the algorithm to facilitate efficient use of the container space. In addition, the proposed algorithm covers an important constraint called shipment priority to solve practical problems. The validity of the proposed algorithm is examined by comparing the present results with those of published algorithms using the same data.     

D-最优设计的分部搜索数值构造方法

为了简化D-最优设计的过程,便于工程应用,提出了一种D-最优设计的数值构造方法——分部搜索数值构造方法。该方法以惯性器件测试为背景,以D-最优性为准则,将传统的D-最优设计分解为谱点寻优和测度寻优两个部分,降低了设计的复杂度,从而减少了运算量,又具有操作简单、思路清楚直观的特点,工程实用性强。提出并证明了相关的定理及推论,从理论上说明了这种构造方法的正确性。以陀螺加速度计误差模型系数辨识试验为例,运用此算法进行了D-最优设计。设计的结果证明了该方法的正确性,同直接搜索法相比,能将最小设计维数降低为原来的50%,提高了设计效率。     

Pattern recognition of Chinese flue-cured tobaccos by an improved and simplified K-nearest neighbors classification algorithm on near infrared spectra

In tobacco industry of China, tobacco leaves are classified and managed in terms of their cultivation areas and plant parts of tobacco-stalks. However, sometimes intentionally or involuntary mislabeling cultivation areas, blending tobacco plant parts would occur into tobacco market. The error will affect the style and quality of cigarettes. In the present work, more than 1000 Chinese flue-cured tobacco leaf samples, which have 12 genotypes and cultivated from 5 to 10 regions of China in 2003 and 2004, have been discriminated by means of an improved and simplified KNN classification algorithm (IS-KNN) based on near infrared (NIR) spectra. An original method of optimizing number of significant principal components (PCs) based on analysis of error and cross-validation was advanced. Compared with conventional pattern recognition methods KNN, NN, LDA and PLS-DA, IS-KNN exhibits good adaptability in discrimination of complicated Chinese flue-cured tobaccos. The practice in this work shows that optimized number of PCs and performance of classification models are closely relative to complicated extent of samples but not to number of categories or samples. The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method for the authentication and identification of tobacco leaves or other kinds of powder samples.     

Theoretical study of preparative chromatography using closed-loop recycling with an initial gradient

Complementing classical isocratic elution, several more sophisticated operating modes have been proposed and are applied in preparative chromatography in order to improve performance. One such approach is gradient elution, where the solvent strength is altered by varying the fraction of a modifier added to the mobile phase to enhance selectivity and to achieve faster elution. Another useful technique is closed-loop recycling, allowing better peak resolution and increased yields. This study focuses on a modified new scheme which incorporates the advantages of both gradient elution and closed-loop recycling for the separation of a ternary mixture where the intermediately eluting component is the target. A parametric study was carried out using typical adsorption isotherm parameters to elucidate the effects of varying loading factors and parameters specific to the two basic operational modes on production rates and yields. A comparison was also made between the proposed scheme and conventional techniques. It was found that the studied scheme could exploit increased column loadings and offers significantly higher production rates.