多目标运输问题的Fuzzy线性规划解法

经典运输问题是一类特殊的单目标线性规划问题，可用表上作业法或单纯形法求其最优解。近年来，许多学研究了多目标运输问题，提出了相应的求解算法。本应用Fuzzy线性规划的方法，给出了多目标运输问题的又一求解算法。     

多目标规划的光滑同伦方法

本文给出了求解多目标规划的一种连续同伦方法 .首先 ,运用光滑熵函数将多目标多约束的问题化为单目标单约束的问题 ,然后构造了求解单目标问题的同伦方法 ,并证明了其大范围收敛性 .     

多目标线性生产规划的模糊联盟对策

研究多目标生产规划的模糊联盟对策的求解问题,提出了求解多目标模糊联盟对策的Shapley值方法.通过建立多目标线性生产规划的模糊联盟对策模型,提出了多目标对策转化为多个单目标对策的权重分析法.结合多目标线性生产规划问题的实例,给出不同权重系数下局中人合作的利益分配策略.     

一种求解多层多目标系统非劣决策的实用算法

本文基于反馈系统理论知识 ,提出了求解多层多目标决策系统的非劣决策的一种实用算法 ,此算法是对求解单层多目标决策系统非劣解的加权法的推广     

具有模糊信息的多目标运输问题求解

提出一种求解具有模糊信息的多目标运输问题的方法。利用专家意见通过模糊算法集给从各产地到各目的地运送单位物资的模糊综合指标值,运用一种对模糊数排序的方法,将模糊多目标运输问题转化为单目标的运输问题进行求解,最后给出了一个数值例子。     

多目标装配线平衡的优化算法

在生产制造系统中，装配线的平衡需要针对多个目标，传统的装配线平衡问题，优化单一目标，忽略了目标之间的联系。优化一个目标的同时，劣化了另外一个目标。章研究了多目标装配线平衡问题，探讨了这些目标之间的联系，设计了禁忌搜索算法求解多目标装配线的平衡问题。章从生产管理系统的角度优化多目标装配线平衡，与单一目标相比，具有显的改进。     

基于部件指派的多状态系统可靠度优化研究

针对一般二态系统假设的不足,提出了多状态系统条件下的可靠度优化指派问题。该问题以系统可靠度最大化为优化目标,在考虑部件分配成本和总分派成本预算的前提下,对多状态系统下不同状态对应的性能水平的进行了分析,给出了基于通用生成函数的多状态系统的可靠度评估方法。根据指派问题的组合优化的特性和多状态系统可靠性评估的特点,对传统遗传算法的适应度函数进行了改进,设计了基于整数编码的遗传算法,该算法具有离散变量的设计灵活性和强大的搜索性能。算例实验表明,本文设计的优化算法具有较好的求解质量,同时算法的运行时间也得到了大幅的缩短。本研究为多状态系统的可靠度优化提供了一条可借鉴的思路。     

线性等式约束多目标规划的一个降维算法

本文提出具有线性等式约束多目标规划问题的一个降维算法．当目标函数全是二次或线性但至少有一个二次型时，用线性加权法转化原问题为单目标二次规划，再用降维方法转化为求解一个线性方程组．若目标函数非上述情形，首先用线性加权法将原问题转化为具有线性等式约束的非线性规划，然后，对这一非线性规划的目标函数二次逼近，构成线性等式约束二次规划序列，用降维法求解，直到满足精度要求为止．     

多目标模糊系数规划

在单目标模糊系数规划的理论基础上，对多目标模糊系数规划进行讨论，在以目标间的协调程度尽可能大为最优性条件的要求下提出多目标模糊系数规划最优解的定义，并给出一种可行的求解方法。     

物流运输网络多目标最短路问题的模糊满意解

本文对物流运输网络多目标最短路问题进行了研究。提出了一种求解多目标最短路问题的目标集成方法和对集成后目标函数求解的扩展标号法。在将多目标转化为单目标时,综合考虑了每个目标的边缘评价和所有目标的整体评价因素,通过对每个目标的权重分配将决策者的偏好充分体现到决策过程中,采用广义的模糊目标集成算子形成了相应的折衷规划模型。最后,通过实例对本文所提方法进行了说明。     

基于遗传算法的多目标可靠性优化

在元件的体积、重量和造价的共同约束下的多级串并联系统的可靠性优化问题是一个具有多局部极值的、非线性的、同时具有整数和实数变量的混合优化问题.将遗传算法和多目标可靠性分配问题相结合,对可靠性分配问题进行求解,得到较好效果,从而得出结论,遗传算法在求解多目标可靠性优化问题中是一种行之有效的方法.     

Characterisation of multiple conducting permeable objects in metal detection by polarizability tensors

Realistic applications in metal detection involve multiple inhomogeneous‐conducting permeable objects, and the aim of this paper is to characterise such objects by polarizability tensors. We show that, for the eddy current model, the leading order terms for the perturbation in the magnetic field, due to the presence of N small conducting permeable homogeneous inclusions, comprises of a sum of N terms with each containing a complex symmetric rank 2 polarizability tensor. Each tensor contains information about the shape and material properties of one of the objects and is independent of its position. The asymptotic expansion we obtain extends a previously known result for a single isolated object and applies in situations where the object sizes are small and the objects are sufficiently well separated. We also obtain a second expansion that describes the perturbed magnetic field for inhomogeneous and closely spaced objects, which again characterises the objects by a complex symmetric rank 2 tensor. The tensor's coefficients can be computed by solving a vector valued transmission problem, and we include numerical examples to illustrate the agreement between the asymptotic formula describing the perturbed fields and the numerical prediction. We also include algorithms for the localisation and identification of multiple inhomogeneous objects.     

Efficient coordinated motion

The problem of efficiently coordinating the motion of multiple objects is examined. It is assumed that there is sufficient space without objects to guarantee a solution. For simplifying the analysis, we also consider all objects to have the same size. A new divide-and-solve technique is proposed for addressing coordinated motion problems. The algorithm suggested divides a problem into subproblems, solves the smaller problems locally, exchanges objects across the local boundaries, and repeats the process until the desired configuration is achieved. It is shown that the average complexity of such an algorithm is much better compared to naive methods for solving this problem.     

Finding multiple roots of a box-constrained system of nonlinear equations with a biased random-key genetic algorithm

Several numerical methods for solving nonlinear systems of equations assume that derivative information is available. Furthermore, these approaches usually do not consider the problem of finding all solutions to a nonlinear system. Rather, most methods output a single solution. In this paper, we address the problem of finding all roots of a system of equations. Our method makes use of a biased random-key genetic algorithm (BRKGA). Given a nonlinear system, we construct a corresponding optimization problem, which we solve multiple times, making use of a BRKGA, with areas of repulsion around roots that have already been found. The heuristic makes no use of derivative information. We illustrate the approach on seven nonlinear equations systems with multiple roots from the literature.     

A just-in-time three-level integrated manufacturing system for linearly time-varying demand process

This paper considers a just-in-time (JIT) manufacturing system in which a single manufacturer procures raw materials from a single supplier, process them to produce finished products, and then deliver the products to a single-buyer. The customer demand rate is assumed to be linearly decreasing time-varying. In the JIT system, in order to minimize the suppliers as well as the buyers holding costs, the supply of raw materials and the delivery of finished products are made in small quantities. In this case, both the supply and the delivery may require multiple installments for a single production lot. We develop a mathematical model for this problem, propose a simple methodology for solving the model, and illustrate the effectiveness of the method with numerical examples.     

Quasi-linear stochastic programming model based on expectation and variance and its application in transportation problem

The stochastic transportation problem involves in many areas such as production scheduling, facility location, resource allocation, logistics management. Constructing an operable solving method has important theoretical and practical value. In this paper, we first analyze the characteristic and deficiencies of the existing stochastic programming methods, such as higher computation complexity. We then give the concept of reliability coefficient and a quasi-linear processing pattern based on expectation and variance. We further analyze the relationship between reliability coefficient and reliability degree, also give the selecting strategy of reliability coefficient. Based on that, we establish a quasi-linear programming model for stochastic transportation problem, and we analyze its performance by a case-based example. The results indicate that this model has good interpretability and operability. It can effectively solve the transportation problem under complex stochastic environment or with incomplete information.     

A variational method using fractional order Hilbert spaces for tomographic reconstruction of blurred and noised binary images

We provide in this article a refined functional analysis of the Radon operator restricted to axisymmetric functions, and show that it enjoys strong regularity properties in fractional order Hilbert spaces. This study is motivated by a problem of tomographic reconstruction of binary axially symmetric objects, for which we have available one single blurred and noised snapshot. We propose a variational approach to handle this problem, consisting in solving a minimization problem settled in adapted fractional order Hilbert spaces. We show the existence of solutions, and then derive first order necessary conditions for optimality in the form of optimality systems.     

Reliability and cost analysis of series system models using fuzzy parametric geometric programming

In this paper, we have discussed series system models with system reliability and cost. We have considered two types of the model; the former focuses on a problem of optimal reliability for series system with cost constraint and the latter is a center system cost model with reliability goal. It is necessary to improve the reliability of the system under limited available cost of system and also to minimize the systems cost subject to target goal of the reliability. Practically, cost of components has always been imprecise with vague in nature. So they are taken as fuzzy in nature and the reliability models are formulated as a fuzzy parametric geometric programming problem. Numerical examples are given to illustrate the model through fuzzy parametric geometric programming technique.     

RELIABILITY ANALYSIS FOR A REPAIRABLE PARALLEL SYSTEM WITH TIME-VARYING FAILURE RATES

To solve a real problem :how to calculate the reliability of a system with time-varying failure rates in industry systems,this paper studies a model for the load-sharing parallel system with time-varying failure rates,and obtains calculating formulas of reliability and availability of the system by solving differential equations. In this paper, the failure rates are expressed in polynomial configuration. The constant,linear and Weibull failure rate are in their special form. The polynomial failure rates provide flexibility in modeling the practical time-varying failure rates.     

General fractional variational problem depending on indefinite integrals

In this report, we consider two kind of general fractional variational problem depending on indefinite integrals include unconstrained problem and isoperimetric problem. These problems can have multiple dependent variables, multiorder fractional derivatives, multiorder integral derivatives and boundary conditions. For both problems, we obtain the Euler-Lagrange type necessary conditions which must be satisfied for the given functional to be extremum. Also, we apply the Rayleigh-Ritz method for solving the unconstrained general fractional variational problem depending on indefinite integrals. By this method, the given problem is reduced to the problem for solving a system of algebraic equations using shifted Legendre polynomials basis functions. An approximate solution for this problem is obtained by solving the system. We discuss the analytic convergence of this method and finally by some examples will be showing the accurately and applicability for this technique.