A Primal-Dual Infeasible-Interior-Point Algorithm for Multiple Objective Linear Programming Problems

A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness.

THREE-IMAGE MATCHING FOR 3-D LINEAR OBJECT TRACKING

This paper will discuss strategies for trinocular image rectification and matching for linear object tracking.It is well known that a pair of stereo images generates two epipolar images.Three overlapped images can yield six epipolar images in situations where any two are required to be rectified for the purpose of image matching.In this case,the search for feature correspondences is computationally intensive and matching complexity increases.A special epipolar image rectification for three stereo images,which simplifies the image matching process,is therefore proposed.This method generates only three rectified images,with the result that the search for matching features becomes more straightforward.With the three rectified images,a particular line_segment_based correspondence strategy is suggested.The primary characteristics of the feature correspondence strategy include application of specific epipolar geometric constraints and reference to three_ray triangulation residuals in object space.

Determining Efficient Solutions of Multi-Objective Linear Fractional Programming Problems and Application

In this paper, a modified method to find the efficient solutions of multi-objective linear fractional programming (MOLFP) problems is presented. While some of the previously proposed methods provide only one efficient solution to the MOLFP problem, this modified method provides multiple efficient solutions to the problem. As a result, it provides the decision makers flexibility to choose a better option from alternatives according to their financial position and their level of satisfaction of objectives. A numerical example is provided to illustrate the modified method and also a real life oriented production problem is modeled and solved.

Randomized Objective Function Linear Programming in Risk Management

The traditional linear programming model is deterministic. The way that uncertainty is handled is to compute the range of optimality. After the optimal solution is obtained, typically by the simplex method, one considers the effect of varying each objective function coefficient, one at a time. This yields the range of optimality within which the decision variables remain constant. This sensitivity analysis is useful for helping the analyst get a sense for the problem. However, it is unrealistic because objective function coefficients tend not to stand still. They are typically profit contributions from products sold and are subject to randomly varying selling prices. In this paper, a realistic linear program is created for simultaneously randomizing the coefficients from any probability distribution. Furthermore, we present a novel approach for designing a copula of random objective function coefficients according to a specified rank correlation. The corresponding distribution of objective function values is created. This distribution is examined directly for central tendency, spread, skewness and extreme values for the purpose of risk analysis. This enables risk analysis and business analytics, emerging topics in education and preparation for the knowledge economy.

Diagnosis and Resolution of Infeasibility in the Constraint Method for Solving Multi Objective Linear Programming Problems

In this paper we discuss about infeasibility diagnosis and infeasibility resolution, when the constraint method is used for solving multi objective linear programming problems. We propose an algorithm for resolution of infeasibility, which is a combination of interactive, weighting and constraint methods.Numerical examples are provided to illustrate the techniques developed.

Two-Phase Multi Objective Fuzzy Linear Programming Approach for Sustainable Irrigation Planning

The objective of the present study is to develop the irrigation planning model and to apply the same in the form of Two-Phase Multi Objective Fuzzy Linear Programming (TPMOFLP) approach for crop planning in command area of Jayakwadi Project Stage I, Maharashtra State, India. The development of TPMOFLP model is on the basis of various Linear Programming (LP) models and Multi Objective Fuzzy Linear Programming (MOFLP) models, these models have been applied for maximization of the Net Benefits (NB), Crop production (CP), Employment Generation (EG) and Manure Utilization (MU) respectively. The significant increase in the value of level of satisfaction (λ) has been found from 0.58 to 0.65 by using the TPMOFLP approach as compare to that of MOFLP model based on maxmin approach. The two-phase approach solution provides NB = 1503.56 Million Rupees, CP = 335729.30 Tons, EG = 29.74 Million Man days and MU = 160233.70 Tons respectively. The proposed model will be helpful for the Decision Maker (DM) to take a decision under conflicting situation while planning for different conflicting objectives simultaneously and has potential to find out an integrated irrigation planning with prime consideration for economic, social and environmental issue.

Solving Multi-Objective Linear Programming Problem by Statistical Averaging Method with the Help of Fuzzy Programming Method

A multi-objective linear programming problem is made from fuzzy linear programming problem. It is due the fact that it is used fuzzy programming method during the solution. The Multi objective linear programming problem can be converted into the single objective function by various methods as Chandra Sen’s method, weighted sum method, ranking function method, statistical averaging method. In this paper, Chandra Sen’s method and statistical averaging method both are used here for making single objective function from multi-objective function. Two multi-objective programming problems are solved to verify the result. One is numerical example and the other is real life example. Then the problems are solved by ordinary simplex method and fuzzy programming method. It can be seen that fuzzy programming method gives better optimal values than the ordinary simplex method.

Solving Fuzzy Multi-Objective Linear Programming Problem by Applying Statistical Method

In this paper, the statistical averaging method and the new statistical averaging methods have been used to solve the fuzzy multi-objective linear programming problems. These methods have been applied to form a single objective function from the fuzzy multi-objective linear programming problems. At first, a numerical example of solving fuzzy multi-objective linear programming problem has been provided to validate the maximum risk reduction by the proposed method. The proposed method has been applied to assess the risk of damage due to natural calamities like flood, cyclone, sidor, and storms at the coastal areas in Bangladesh. The proposed method of solving the fuzzy multi-objective linear programming problems by the statistical method has been compared with the Chandra Sen’s method. The numerical results show that the proposed method maximizes the risk reduction capacity better than Chandra Sen’s method.

IDENTIFICATION OF 3-D OBJECTS FROM THREE ORTHOGONAL SILHOUETTES USING NORMALIZED LINEAR QUAD-OCTREES

Linear octrees offer a volume representation of 3-D objects, which is quite compactand lends itself to traditional object processing operations. However, the linear octree structurefor generating the representation of 3-D objects from three orthogonal silhouettes by using thevolume intersection technique is dependent on viewpoints. The recognition achieved from match-ing object representations to model representations requires that the representations of objectsare independent of viewpoints. In order to obtain independent representations of viewpoints,the three principal axes of the object should be obtained from the moment of inertia matrix bycomputing its eigenvectors. The linear octree is projected onto the image planes of the three prin-cipal views (along the principal axes) to obtain the three normalized linear quadtrees. The objectmatching procedure has two phases: the first phase is to match the normalized linear quadtrees ofthe unknown object to a subset of models contained in a library utilizing a measure of symmetricdifference; the second phase is to generate the normalized linear octrees of the object and theseselected models and then to match the normalized linear octree of the unknown object with themodel having the minimum symmetric difference.

基于SuperMap Objects线状地物面积快速扣除算法实现

线状地物调查是土地资源调查中的一项重要内容。在分类统计汇总土地面积时,计算、扣除线状地物面积时显得尤为重要。本文在分析线状地物与地类图斑空间关系的基础上,设计了线状地物面积快速扣除算法。利用SuperMap Objects作为开发平台,VC++6.0为开发工具实现了该算法。经验证,该算法能够快速实现线状地物面积扣除,可达到相关建库工作的精度要求。

基于Linear Sampling方法的二维可穿透区域反演

提出用时间调和声散射远场信息来反演二维可穿透目标的一种Linear Sampling方法,通过提取包含可穿透目标的一个样本区域的支集的点列来实现反演的,因为其在区域内与区域外有显著的不同取值,由此而获得区域的逼近.这个算法特别吸引人之处是不需关于障碍物的任何先验信息.并且只需散射场在某个有限孔径中的部分远场信息,即可获得穿透区域的一个逼近.一些数值算例保证了这个反演算法是有效的和实用的.

Optimal Irrigation Planning and Operation of Multi Objective Reservoir Using Fuzzy Logic

In the present study the MOFLP models have been developed for the optimal cropping pattern planning which maximizes the four objectives such as Net Benefits (NB), Crop Production (CP), Employment Generation (EG) and Manure Utilization (MU) under conflicting situation and also, for maximization of Releases for Irrigation (RI) and Releases for Power (RP) simultaneously under uncertainty by considering the fuzziness in the objective functions. The developed models have been applied using the LINGO 13 (Language for Interactive General Optimization) optimization software to the case study of the Jayakwadi Project Stage-II across Sindhphana River, in the State of Maharashtra India. The various constraints have been taken into consideration like sowing area, affinity to crop, labour availability, manure availability, water availability for optimal cropping pattern planning. Similarly constraints to find the optimal reservoir operating policy are releases for power and turbine capacity, irrigation demand, reservoir storage capacity, reservoir storage continuity. The level of satisfaction for a compromised solution of optimal cropping pattern planning for four conflicting objectives under fuzzy environment is worked out to be λ = 0.68. The MOFLP compromised solution provides NB = 1088.46 (Million Rupees), CP = 241003 (Tons), EG = 23.13 (Million Man days) and MU = 111454.70 (Tons) respectively. The compromised solution for optimal operation of multi objective reservoir yields the level of satisfaction (λ) = 0.533 for maximizing the releases for irrigation and power simultaneously by satisfying the constraint of the system under consideration. The compromised solution provides the optimal releases, i.e. RI = 348.670 Mm3 and RP = 234.285 Mm3 respectively.

An Approach to Solve a Possibilistic Linear Programming Problem

The objective of the paper is to deal with a kind of possibilistic linear programming (PLP) problem involving multiple objectives of conflicting nature. In particular, we have considered a multi objective linear programming (MOLP) problem whose objective is to simultaneously minimize cost and maximize profit in a supply chain where cost and profit coefficients, and related parameters such as available supply, forecast demand and budget are fuzzy with trapezoidal fuzzy numbers. An example is given to illustrate the strategy used to solve the aforesaid PLP problem.

基于装卸顺序的中型机多航段协同配载优化

多航段、多经停的航空货运航班,飞行过程中需要合理控制飞机的重心(CG)位置,保持平衡状态,中转站装卸操作过程中需要避免额外装卸操作,减少时间和劳力浪费,因此,研究多航段航班的协同配载问题具有重要现实意义。根据航空器自身特点与集装器(ULD)装卸顺序,结合各航段飞机装载平衡与过站机场ULD装卸操作要求,通过协调分配各航段ULD和散货位置,建立了中型机联程航班多目标整数线性规划模型。模型考虑了ULD和散货的质量、体积及与舱位的匹配限制,航空器限重、舱位限重、舱位及区域累积限重、上下舱联合限重和CG位置的平衡限制,以及前后航段ULD和散货的连接性约束。根据造成中间机场额外装卸操作的2种原因,基于装卸顺序,提出装卸优化模型,通过ULD的舱内平移,优化了CG,减少了装卸次数。以B757-200F机型为例,在两装一卸、一装两卸和两装两卸3种场景下,采用商用求解器Gurobi,分别针对3种不同目标函数组合进行求解和分析对比。实验表明:所提模型可以有效协调过站货物的额外装卸次数,优化前后两航段的CG位置。

FUZZY IDENTIFICATION METHOD BASED ON A NEW OBJECTIVE FUNCTION

A method of fuzzy identification based on a new objective function is proposed. The method could deal with the issue that input variables of a system have an effect on the input space while output variables of the system do not exert an influence on the input space in the proposed objective functions of fuzzy clustering. The method could simultaneously solve the problems about structure identification and parameter estimation; thus it makes the fuzzy model become optimal. Simulation example demonstrates that the method could identify non linear systems and obviously improve modeling accuracy.

基于RSM-正交法的磁障式直线永磁游标电机的设计与优化

针对直线永磁游标电机的损耗问题,提出一种磁障式拓扑结构。通过在次级的凸极齿加入隔磁磁障,使次级对磁通的流动具有导向作用,减少涡流损耗,提高电机的磁场调制能力。在此基础上,设计一种磁障式直线永磁游标电机,采用响应面(RSM)-正交法对电机的推力性能进行优化。首先,通过对电机进行灵敏度分析,确定显著变量。其次,根据RSM法建立优化目标响应与显著变量之间的拟合模型,并对其拟合精度进行评估。最后,基于该模型进行正交试验,根据正交试验的数据进行极差分析,得到电机的最优结构参数。有限元实验结果表明,采用RSM-正交优化方法的电机性能得到大幅提高,并且可以节省优化时间,提高优化效率,对直线永磁游标电机的设计与优化有重要的参考价值。

基于改进粒子群算法的主动配电网无功优化

随着分布式电源在配电网中的广泛应用,部分地区电压越限、有功网损增加的现象时有发生。但传统算法求解无功优化无法适应当代配电网的要求。因此,提出一种改进的粒子群算法应用于主动配电网无功优化。首先,建立有功损耗、电压偏移和、节点最低电压值的多目标函数,通过线性加权求和的方法将多目标函数转换为单目标。然后,提出一种基于种群集中度概念的惯性权重调整,并在算法的学习因子中引入正弦和余弦控制因子,利用改进后的算法进行主动配电网无功优化。最后,在改进的IEEE33节点上进行仿真,验证所提出算法的可行性、有效性。

考虑梯级水电融合抽蓄改造的风光资源多目标容量配置

为实现梯级水风光蓄联合发电系统高效多能互补,研究考虑梯级水电融合抽蓄改造的风光发电多目标容量优化配置方法。以联合发电系统外送通道利用率最大和受端电网剩余负荷峰谷差最小为目标,优化联合发电系统风电和光伏发电的配置容量;考虑风电和光伏发电季节性波动,基于K-means聚类构建风电和光伏发电出力的典型场景,提出了梯级水风光蓄全场景互补运行模型,并发展了便于快速求解的混合整数线性化模型。以小金川梯级小水电周边的风电场与光伏电站为例,对所提方法的有效性进行了验证,分析了梯级水风光蓄联合系统的互补性,对比说明了混合式抽蓄在联合发电系统中的作用。

基于空间异质运算的结构信息提取辅助遥感影像分类研究

以Landsat-8和高分一号数据为例,采用仅有光谱特征、3种纹理特征(概率统计、灰度共生矩阵、空间异质运算)辅助光谱特征的方法提取影像空-谱信息,并通过支持向量机分类器进行基于像元的地物分类。结果表明:1)纹理特征辅助光谱特征的地物分类精度明显优于仅使用光谱特征的分类,可提高8.62%~24.36%;2)相较于概率统计、灰度共生矩阵方法结果,空间异质运算结果分类精度在GF-1影像中分别提高了13.31%和2.03%,在Landsat-8影像中分别提高了11.62%和7.79%;3)对于线状地物,相较于概率统计、灰度共生矩阵方法结果,空间异质运算结果分类精度在GF-1数据中分别提高了29.31%和0.80%,在Landsat-8数据中分别提高了11.90%和6.64%,有效减小了分类误差。因此,空间异质运算提取的空间结构信息辅助光谱特征的分类方法能显著改善遥感图像的分类精度,为空间结构信息辅助遥感影像地物分类及线状地物的提取提供一种新的思路和方法。

Sustainable Multi-Objective Multi-Reservoir Optimization Considering Environmental Flow

Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.