基于Stackelberg博弈策略下的多渠道供应链决策研究

构建了基于价格竞争的多渠道供应链模型,模型中两个不同的制造商分别通过单渠道、双渠道销售具有一定替代性的产品,考虑到制造商在市场上的领导地位,制造商与零售商之间采用stackclberg博弈竞争策略.探讨了拥有双渠道的制造商采取分散和集中利润决策时供应链各竞争者的价格策略,分析了需求函数参数变化对供应链竞争者价格决策的影响,借助算例分析表明,拥有双渠道营销方式的制造商采取决策1有利于提高其所在供应链的利润,采用决策2能够激励零售商维持原有的分销渠道.     

基于拼团模式的网络团购定价策略

随着移动互联网的发展,拼团模式受到越来越多零售商和消费者的追捧.以传统商业团购模型为基础,引入团购尺寸、发起者精力成本、需求扩散效应和拼团成功率,建立了零售商同时采取线上拼团和线下传统渠道策略的两阶段利润优化模型.运用Stackelberg博弈模型求解零售商和团购网站之间的利润分配问题,得出了零售商和团购网站的最优定价策略.通过算例分析了各因素对零售商和团购网站最优决策及利润的影响,对比分析了传统商业团购与拼团模式,据此给出了相关各方决策建议.     

Fuzzy概率理论用于研究采矿引起的岩体移动

本文运用 Fuzzy 概率理论,对矿山岩体力学中的岩体移动问题,建立了相应的Fuzzy 数学模型,并利用该模型对地下采矿导致的岩体垂直移动、水平移动、水平变形、岩体倾斜和曲率变化等指标进行了定量计算.对于山区开采导致的岩体移动问题也进行了初步探讨.最后还对几个矿山工程实例进行了计算分析,结果表明,本文提出的新方法可用于分析采矿导致的岩体移动问题.     

O2O实体渠道与网络渠道价格差异的竞争分析

针对由O2O实体渠道和网络渠道集成的双渠道供应链,在Hotelling模型基础上先构建出消费者效用函数模型和需求函数模型,然后建立双渠道收益函数模型,并求解分析电子商务成熟度、购物成本、服务质量对两种渠道价格差异的影响.结果表明,电子商务成熟度超过一个临界值时,网络渠道价格将高于O2O实体渠道;网上购物成本越高,网络渠道价格低于O2O实体渠道;服务质量越高,利润越大.最后,将收集的相关指标数据进行假设检验和多元线性回归分析,实证结果与理论分析相符.因此,研究对分析这两种渠道的定价差异具有指导意义.     

B2C模式下双渠道供应链定价策略研究

随着B2C模式的电子商务的发展与成熟,越来越多的企业引入了在线直销渠道与在线零售渠道的双渠道营销模式.如何制定有效的在线双渠道定价策略,实现不同在线渠道利益的均衡和渠道整体效益的最大化,成为企业需要解决的实际问题.构建了消费者效用函数模型和双渠道定价决策博弈模型,考察了消费者选择渠道的隐性成本和对在线渠道服务水平满意程度对双渠道定价决策的影响,对比了在线零售商与在线直销制造商分别在独立决策,零售商占主导地位和供应链纵向一体化的三种情况下的双渠道供应链定价策略.最后借助Matlab软件对决策模型进行了计算与仿真,为在线渠道内供应链中各成员的管理者制定最优的定价策略提供决策支持.     

制造商质量投入竞争与合作的双渠道供应链动态博弈研究

针对具有不同质量投入和服务投入的双渠道供应链,主要研究其成员最优均衡决策问题.构建了包含两个制造商和一个零售商的两级双渠道供应链决策模型;采用微分博弈确定在制造商竞争和合作两种模型下各成员的最优均衡决策及其利润,并着重探讨质量投入系数、服务竞争系数和传统渠道市场占有率这三个关键参数对它们的影响;用算例对该模型进行仿真分析研究结果表明:在竞争模型下零售商的利润随着传统渠道市场占有率、质量投入竞争和服务竞争的增大而增大,但合作模型下的利润与服务竞争无关;制造商合作时制造商的利润之和提高,且两个制造商在两个渠道边际利润和之比在一定范围内,两个制造商会有合作意愿,但零售商的利润下降.研究能够为各成员企业的最优均衡决策提供支持和参考.     

考虑供应链渠道冲突的零售商自有品牌产品定价方法

自有品牌产品定价是电子商务环境下零售商实施渠道管理的关键因素,其合理与否直接影响到零售商利润和供应链稳定.鉴于此,针对存在供应链渠道冲突的零售商自有品牌定价问题,从协调的角度,利用对偶理论与优化模型,构建了基于最小协调成本的零售商自有品牌产品定价决策方法,并利用其探讨协调的经济意义,求解零售商自有品牌产品最优定价.结果表明,所构建的模型能够有效描述和解决零售商自有品牌产品定价问题,并在一定程度上消除供应链渠道冲突,保证供应商和零售商长期有效合作和供应链可持续发展.     

基于特定群体的移动商务消费者信任影响因素分析

消费者信任是影响移动商务发展的关键因素,针对国内移动商务发展的现状,构建了以高校大学生为研究对象的移动商务消费者信任影响因素模型,模型包括消费者个人、产品、移动商家、移动技术、网站媒介以及制度保障6个方面的内容,并据此设计了网络调查问卷,累计收集了219份有效数据.实证分析表明:对高校大学生而言,移动终端设备的易用性是影响消费者信任最关键的因素,其次是消费者对移动互联网和移动商家的熟悉程度,第三是移动商务产品的价格差异;最后根据数据分析结果提出了改善移动商务消费者信任的建议.     

轮式移动舞台机器人双模模型预测控制北大核心CSCD

针对轮式移动舞台机器人的快速镇定和移动区域约束控制问题,提出一种快速双模模型预测控制(MPC)算法.考虑轮式移动舞台机器人的位姿约束和速度约束,采用控制Lyapunov函数概念和极坐标系模型设计模型预测控制算法.利用移动舞台机器人与目标的距离、瞄准角和方位角构造一个控制Lyapunov函数,建立移动舞台机器人的一个解析双模结构MPC控制器,再引入自由变量,参数化预测控制变量,降低双模MPC在线优化计算量.在约束条件下,建立了轮式移动舞台机器人闭环系统稳定性和MPC递推可行性理论结果.最后,通过与常规MPC比较,仿真验证所提算法的有效性和优越性.     

寡头竞争模型在旅游联盟协议中的应用

博弈论中的寡头竞争模型在经济、政治、军事等社会科学中得到了广泛的应用.针对旅游联盟的机会主义行为,以库诺特(Cournot)寡头竞争模型为基础建立了旅游联盟博弈模型,来分析旅游联盟建立正式协议的必要性,并探讨了联盟协议的主要内容,包括:联盟的战略目标和合作范围;投入资源评价与利益分配;交流渠道;联盟解散条款.最后指出了建立协议的协商原则和灵活性原则.     

基于遗传算法的多通道密集式移动货架订单拣选研究

密集式移动货架越来越多地应用到仓储实践中,提高了仓储空间利用率,但增加了订单拣选的时间成本。本文根据密集式移动货架的仓储布局特点,针对多条通道可同时打开的情况,将货架移动时间转换成通道移动距离进行计算,提出了多条通道依次移动的优化规则,以整批订单拣选所耗费的总时间最少为目标,建立了订单拣选顺序优化的数学模型。针对该模型的特点,设计了实数编码且全局寻优的遗传算法,并进行了不同规模的算例模拟。计算结果表明,该算法具有较强的适用性,针对不同规模的问题,均有显著的优化效果;货架数量、订单数量以及移动通道数量的小幅度增减,将会导致总拣选时间较大幅度的波动;多条移动通道初始位置居于中部或均匀分散,总拣选时间略优于其集中于仓储系统一端。     

Optimization of rod antennas of mobile phones

Two types of rod antennas of mobile phones are optimized so that the radiated energy absorbed by the head or body of the user is reduced and the radiation intensity to other areas especially to the receiver is increased. The mathematical modelling of this problem leads to an infinite dimensional bicriterial optimization problem. It is shown that this optimization problem and a discretized version of this problem are solvable. The relationship between the infinite and finite dimensional optimization problem is investigated. Numerical results are presented for mobile phones working with the GSM standards 900 and 1800.     

Sizing initial stockpiles in a conventional military retrograde movement

The importance of stockpiles in waging and supporting war has long been recognized by the military. However, despite this recognition, very few theoretical attempts have been undertaken to incorporate stockpile considerations in land combat models. This paper describes a multicriteria optimization model to estimate the minimum stockpile required to sustain fighting a conventional mobile delaying land battle. By studying the post-optimality analysis, valuable insights on the relationships between the key governing parameters can be established.     

Neuro-fuzzy technique for navigation of multiple mobile robots

In this paper, navigation techniques for several mobile robots are investigated in a totally unknown environment. In the beginning, Fuzzy logic controllers (FLC) using different membership functions are developed and used to navigate mobile robots. First a fuzzy controller has been used with four types of input members, two types of output members and three parameters each. Next two types of fuzzy controllers have been developed having same input members and output members with five parameters each. Each robot has an array of sensors for measuring the distances of obstacles around it and an image sensor for detecting the bearing of the target. It is found that the FLC having Gaussian membership function is best suitable for navigation of multiple mobile robots. Then a hybrid neuro-fuzzy technique has been designed for the same problem. The neuro-fuzzy technique being used here comprises a neural network, which is acting as a pre processor for a fuzzy controller. The neural network considered for neuro-fuzzy technique is a multi-layer perceptron, with two hidden layers. These techniques have been demonstrated in simulation mode, which depicts that the robots are able to avoid obstacles and reach the targets efficiently. Amongst the techniques developed neuro-fuzzy technique is found to be most efficient for mobile robots navigation. Experimental verifications have been done with the simulation results to prove the authenticity of the developed neuro-fuzzy technique.     

贴牌生产供应链混合渠道构建基础及优化机理研究

研究由制造商和品牌商组成的混合渠道贴牌生产供应链渠道结构优化问题,制造商通过直销和贴牌两条渠道销售产品.通过与单一渠道比较,分别推导出制造商和品牌商选择混合渠道的依据和优越性,进而归纳出双方共同接受混合渠道的制造商生产成本和品牌商品牌溢价优化条件,分析了渠道转移系数对双方构建混合渠道结构条件的影响,得出了制造商生产成本和品牌商品牌溢价作为竞争要素的互动决策改进贴牌供应链整体绩效的优化机理.     

Bio-inspired optimization of fuzzy logic controllers for robotic autonomous systems with PSO and ACO

In this paper we describe the use of bio-inspired optimization techniques, such as ant colony optimization and particle swarm optimization, for the design of optimal fuzzy logic controllers of autonomous wheeled mobile robots. The results obtained by the simulations with ant colony optimization and particle swarm optimization are statistically compared with previous optimization results obtained with genetic algorithms in order to find out the best optimization technique for a particular robotics problem.     

基于时间和渠道敏感顾客选择偏好的双渠道定价策略

随着网络技术的发展,带动了网络销售模式的发展。网络渠道为顾客带来了便利性,也为制造商提供了扩大市场占有率和提高利润的机会,如何合理定价关系到企业的长久发展。在考虑顾客对网络渠道交付时间和网络渠道接受敏感的基础上,研究了制造商的单渠道和双渠道定价策略问题。研究结果表明,两种销售模式下零售渠道的定价相同,而网络渠道的定价低于零售渠道的定价。制造商可以通过引入网络渠道提高市场占有率、降低顾客时间敏感性和提高网络渠道接受程度,从而提高利润。最后,通过数值实验分析了交付时间敏感性和网络渠道接受程度对企业决策的影响,并对比分析了单渠道和双渠道的最优决策。     

The application of an oblique-projected Landweber method to a model of supervised learning

This paper brings together a novel information representation model for use in signal processing and computer vision problems, with a particular algorithmic development of the Landweber iterative algorithm. The information representation model allows a representation of multiple values for a variable as well as an expression for confidence. Both properties are important for effective computation using multi-level models, where a choice between models will be implementable as part of the optimization process. It is shown that in this way the algorithm can deal with a class of high-dimensional, sparse, and constrained least-squares problems, which arise in various computer vision learning tasks, such as object recognition and object pose estimation. While the algorithm has been applied to the solution of such problems, it has so far been used heuristically. In this paper we describe the properties and some of the peculiarities of the channel representation and optimization, and put them on firm mathematical ground. We consider the optimization a convexly constrained weighted least-squares problem and propose for its solution a projected Landweber method which employs oblique projections onto the closed convex constraint set. We formulate the problem, present the algorithm and work out its convergence properties, including a rate-of-convergence result. The results are put in perspective with currently available projected Landweber methods. An application to supervised learning is described, and the method is evaluated in an experiment involving function approximation, as well as application to transient signals.     

Accelerating method of global optimization for signomial geometric programming

Signomial geometric programming (SGP) has been an interesting problem for many authors recently. Many methods have been provided for finding locally optimal solutions of SGP, but little progress has been made for global optimization of SGP. In this paper we propose a new accelerating method for global optimization algorithm of SGP using a suitable deleting technique. This technique offers a possibility to cut away a large part of the currently investigated region in which the globally optimal solution of SGP does not exist, and can be seen as an accelerating device for global optimization algorithm of SGP problem. Compared with the method of Shen and Zhang [Global optimization of signomial geometric programming using linear relaxation, Appl. Math. Comput. 150 (2004) 99–114], numerical results show that the computational efficiency is improved obviously by using this new technique in the number of iterations, the required saving list length and the execution time of the algorithm.     

CFD modeling and multi-objective optimization of cyclone geometry using desirability function,artificial neural networks and genetic algorithms

The low-mass loading gas cyclone separator has two performance parameters, the pressure drop and the collection efficiency (cut-off diameter). In this paper, a multi-objective optimization study of a gas cyclone separator has been performed using the response surface methodology (RSM) and CFD data. The effects of the inlet height, the inlet width, the vortex finder diameter and the cyclone total height on the cyclone performance have been investigated. The analysis of design of experiment shows a strong interaction between the inlet dimensions and the vortex finder diameter. No interaction between the cyclone height and the other three factors was observed. The desirability function approach has been used for the multi-objective optimization. A new set of geometrical ratios (design) has been obtained to achieve the best performance. A numerical comparison between the new design and the Stairmand design confirms the superior performance of the new design. As an alternative approach for applying RSM as a meta-model, two radial basis function neural networks (RBFNNs) have been used. Furthermore, the genetic algorithms technique has been used instead of the desirability function approach. A multi-objective optimization study using NSGA-II technique has been performed to obtain the Pareto front for the best performance cyclone separator.