Genetic differentiation and subspecies development of the giant panda as revealed by DNA fingerprinting

Over the last 100 years giant pandas (Ailuropoda melanoleuca) have been separated into six completely isolated mountain ranges. DNA fingerprinting revealed different differentiation patterns in giant pandas, including early-stage, late-stage, recent divergence and recent genetic depression. A separation around 10 000 years ago resulted in highly significant differences in DNA fingerprints and morphological characteristics between Qinling and Sichuan populations. Supported by morphological differences, the genetic data were used to classify the Qinling population as a new subspecies, A. m. qinlingensis, while the Sichuan populations were classified into the original subspecies, A. m. melanoleuca. Thus, the Qinling population deserves management as a separate unit. In the Sichuan populations, two management units were defined, including Qionglai-Minshan and Daxiangling-Xiaoxiangling-Liangshan. Our data suggest urgent measures are needed to establish green corridors between subpopulations in each mountain range to increase gene flow and genetic variation to ensure long-term survival.     

A Point Balance Algorithm for the Spherical Code Problem

The Spherical Code (SC) problem has many important applications in such fields as physics, molecular biology, signal transmission, chemistry, engineering and mathematics. This paper presents a bilevel optimization formulation of the SC problem. Based on this formulation, the concept of balanced spherical code is introduced and a new approach, the Point Balance Algorithm (PBA), is presented to search for a 1-balanced spherical code. Since an optimal solution of the SC problem (an extremal spherical code) must be a 1-balanced spherical code, PBA can be applied easily to search for an extremal spherical code. In addition, given a certain criterion, PBA can generate efficiently an approximate optimal spherical code on a sphere in the n-dimensional space ⁿ. Some implementation issues of PBA are discussed and putative global optimal solutions of the Fekete problem in 3, 4 and 5-dimensional space are also reported. Finally, an open question about the geometry of Fekete points on the unit sphere in the 3-dimensional space is posed.     

Solving Nonconvex Planar Location Problems by Finite Dominating Sets

It is well-known that some of the classical location problems with polyhedral gauges can be solved in polynomial time by finding a finite dominating set, i.e. a finite set of candidates guaranteed to contain at least one optimal location.In this paper it is first established that this result holds for a much larger class of problems than currently considered in the literature. The model for which this result can be proven includes, for instance, location problems with attraction and repulsion, and location-allocation problems.Next, it is shown that the approximation of general gauges by polyhedral ones in the objective function of our general model can be analyzed with regard to the subsequent error in the optimal objective value. For the approximation problem two different approaches are described, the sandwich procedure and the greedy algorithm. Both of these approaches lead - for fixed - to polynomial approximation algorithms with accuracy for solving the general model considered in this paper.     

基于辐射声功率最小化的安静结构设计

本文研究了一种基于模型修改使结构辐射声功率最小的方法，使用了结构动力学、声学和优化理论等学科知识，对结构修改后固有频率变化可以忽略不计时的声辐射优化进行了研究，将设计变量看作外部阻抗，对结构的表面振速进行了重新分布，可以降低结构辐射的声功率。将质量块与动力吸振器进行组合实现声辐射最小化，不但降低了一定频率范围内的平均声功率，还降低了动力吸振器所对应的单频下的声功率；运用遗传算法搜索结构辐射声功率最小时附加质量块或动力吸振器的位置，对附加质量块和有源控制作用下简支钢板的声功率最小化进行了比较研究，阐明了附加外部结构与有源控制实现安静结构的物理机理。最后，对本文提出的基于平板辐射声功率最小化的安静结构设计方法进行了实验验证。     

Genetic Algorithms for Design of Discrete Phase-only Reconfigurable Array Antennas with Fixed Dynamic Range Ratio

In this paper, we present a new method based on real-coded Genetic Algorithm (GA) with elitist model for optimal design of a reconfigurable symmetrical dual-beam uniformly spaced linear isotropic antenna array with phase-only control of quantized phase shifters. The problem is to find a common amplitude distribution that will generate a pencil beam with zero phases and a flat-top beam with discrete phases of a six-bit discrete phase shifter, without or with pre-fixing the value of dynamic range ratio (|I _max/I _min|) of excitation current amplitude distribution equal to or less than five.     

Gain characteristics and optimization of dual-pump fiber optical parametric amplifier using two-section highly nonlinear fibers

In this paper the gain characteristics of two-pump fiber optical parametric amplifiers (FOPA) with two-section highly nonlinear fibers are analyzed numerically and the parameters of the fibers are optimized to reach broad and flat gain spectra using genetic algorithm. Different from the previous methods, here the space between two pump wavelengths and the parameter β₄ of the fibers are included as a pivotal factor in the optimization. The numerical simulation shows that using two-section practical high nonlinear fibers, the amplifier may reach 110 nm bandwidth covering 1495–1605 nm with 10.5 dB average gain and gain ripple of 0.17 dB, when the total pump power is 1 W.     

一种相位提取算法误差特性的分析

设计了一种新的相位提取算法，根据推导的评价函数，研究了其误差特性，与传统相位提取算法做了比较分析，其频域特性有了显著提高．分析结果证明该算法对失谐误差不敏感，高阶偶数谐波误差对结果值也不敏感，具有比较优势．仿真实验结果验证了理论预期．     

Simulated annealing and genetic algorithms for minimizing mean flow time in an open shop

This paper considers the problem of scheduling n jobs on m machines in an open shop environment so that the sum of completion times or mean flow time becomes minimal. It continues recent work by Bräsel et al. [H. Bräsel, A. Herms, M. Mörig, T. Tautenhahn, T. Tusch, F. Werner, Heuristic constructive algorithms for open shop scheduling to minmize mean flow time, European J. Oper. Res., in press (doi.10.1016/j.ejor.2007.02.057)] on constructive algorithms. For this strongly NP-hard problem, we present two iterative algorithms, namely a simulated annealing and a genetic algorithm. For the simulated annealing algorithm, several neighborhoods are suggested and tested together with the control parameters of the algorithm. For the genetic algorithm, new genetic operators are suggested based on the representation of a solution by the rank matrix describing the job and machine orders. Extensive computational results are presented for problems with up to 50 jobs and 50 machines, respectively. The algorithms are compared relative to each other, and the quality of the results is also estimated partially by a lower bound for the corresponding preemptive open shop problem. For most of the problems, the genetic algorithm is superior when fixing the same number of 30 000 generated solutions for each algorithm. However, in contrast to makespan minimization problems, where the focus is on problems with an equal number of jobs and machines, it turns out that problems with a larger number of jobs than machines are the hardest problems.     

A memetic algorithm for multi-objective dynamic location problems

This paper describes a new multiobjective interactive memetic algorithm applied to dynamic location problems. The memetic algorithm integrates genetic procedures and local search. It is able to solve capacitated and uncapacitated multi-objective single or multi-level dynamic location problems. These problems are characterized by explicitly considering the possibility of a facility being open, closed and reopen more than once during the planning horizon. It is possible to distinguish the opening and reopening periods, assigning them different coefficient values in the objective functions. The algorithm is part of an interactive procedure that asks the decision maker to define interesting search areas by establishing limits to the objective function values or by indicating reference points. The procedure will be applied to some illustrative location problems.     

A deterministic,multi-item inventory model with supplier selection and imperfect quality

This paper considers the scenario of supply chain with multiple products and multiple suppliers, all of which have limited capacity. We assume that received items from suppliers are not of perfect quality. Items of imperfect quality, not necessarily defective, could be used in another inventory situation. Imperfect items are sold as a single batch, prior to receiving the next shipment, at a discounted price. The demand over a finite planning horizon is known, and an optimal procurement strategy for this multi-period horizon is to be determined. Each of products can be sourced from a set of approved suppliers, a supplier-dependent transaction cost applies for each period in which an order is placed on a supplier. A product-dependent holding cost per period applies for each product in the inventory that is carried across a period in the planning horizon. Also a maximum storage space for the buyer in each period is considered. The decision maker, the buyer, needs to decide what products to order, in what quantities, with which suppliers, and in which periods. Finally, a genetic algorithm (GA) is used to solve the model.