随机需求下直销多商品流供应链网络均衡模型

建立了随机需求下直销多商品流供应链网络均衡模型,导出了供应链网络达到均衡的条件,它等价于一个有限维变分不等式.通过构建修改拟牛顿法,获得了随机需求下直销多商品流供应链网络均衡模型的解(变分不等式的解),并给出了1个算例,验证了模型的正确性和算法的可行性.     

多商品流供应链网络应对随机需求扰动研究

研究随机需求下多生产商与多零售商组成、生产和销售多种产品的供应链网络如何应对需求扰动问题。利用Nash均衡理论与变分不等式方法,给出了突发事件发生前随机需求多商品流供应链网络供给市场、零售市场和需求市场的均衡条件和经济解释,建立了刻画各层均衡和供应链网络整体均衡的变分不等式模型。当突发事件导致需求扰动,供需矛盾将引起需求市场价格波动和供应链运作风险的激增。分析生产商允许零售商二次订货和退货下供应链网络均衡的变化,建立了基于二次订货与退货合同可应对需求扰动的随机需求多商品供应链网络均衡变分不等式模型。数值算例验证了模型的合理性,表明二次订货与退货合同可有效应对需求扰动。     

基于微分变分不等式的多商品流网络动态模型

针对由多个制造商和多个零售商构成并且具有多商品流的供应链网络,建立了制造商、零售商之间从事微分Nash博弈的供应链网络动态模型.首先,在介绍微分变分不等式定义的基础上,利用微分变分不等式的方法建立了制造商、零售商以及供应链网络的均衡条件.然后,在正则条件下分析了供应链网络动态模型解的存在性条件.最后,利用数值算例验证了模型的合理性.     

网购供应链网络均衡模型研究

本文假设网络零售商和消费者之间商品流既可以通过顾客自提的方式实现,也可以通过快递服务的方式实现,建立了电子商务环境下的网购供应链网络均衡模型,网络中包含四级决策主体,分别是:制造商、网络零售商、快递服务商和消费者。在分析快递服务商的竞争行为的基础上,得到了基于变分不等式的竞争均衡条件。并指出网购消费者的决策行为与一般购物行为存在差异,即网购消费者的决策准则是基于商品价格、快递服务价格和物流配送时间等因素的综合成本函数。综合各级决策者的均衡条件,定义了网购供应链网络系统的整体均衡条件,并给出了经济解释。最后给出算例。     

多商品流多期供应链网络均衡模型

针对具有多种商品流的三层供应链网络结构模型,考虑时间变量和库存问题,分别对制造商、零售商和需求市场的决策者的多期独立决策行为及其相互作用进行了分析,利用变分不等式构建了各层均衡模型以及系统均衡模型,得到了系统达到均衡的条件,给出了具体算例并进行了求解,最后与相关文献的模型进行了比较.     

多目标供应链网络平衡模型

针对生产商、零售商和消费群三层决策者问题建立了一个多目标供应链网络均衡模型.给出此模型的均衡条件,并讨论了(弱)均衡解和标量化解之间的关系.最后,给出具体的例子说明此模型.     

具有随机需求的多种差异产品供应链网络均衡模型研究

针对产品的品牌和产地存在的差异性,研究了供应链网络的均衡模型,构建了具有随机需求的多种差异产品的供应链网络均衡模型.运用随机效用理论和多项式logit模型分析了需求市场上产品的随机选择问题,利用变分不等式的形式给出了制造商、零售商,需求市场以及整个供应链网络的均衡条件,并给出了经济解释.最后,通过算例验证了模型的合理性.     

具有服务水平的差异产品供应链网络均衡模型研究

顾客服务水平已成为当今企业获取较高市场占有率的重要手段。本文考虑了由多个供应商和多个零售商组成的供应链网络模型,通过制造商和零售商提供的服务水平,零售商的订货满足率以及零售价格等因素较为贴切的刻画消费者的选择偏好,利用变分不等式方法分析了制造商、零售商,需求市场以及整个供应链网络均衡条件,并给出了经济解释。最后,通过算例验证了模型的合理性。     

具有模糊需求的闭环供应链网络均衡

利用模糊事件的可信性测度理论、变分不等式理论建立了具有模糊需求的闭环供应链网络均衡模型,其中闭环供应链网络中的制造/再制造工厂存在产能约束,消费市场存在商品限制性价格上限.设计了求解闭环供应链网络均衡解的投影收缩算法,结合数值算例分析了产能约束与限制性价格上限对闭环供应链网络均衡解的影响.结果表明:消费市场中的商品会发生短缺,如果政府对竞争市场实行限制性价格上限,尤其当存在产能约束时商品短缺会更为严重.     

基于再制造的多周期闭环供应链网络均衡模型

针对单周期模型在刻画废旧产品回收和再制造过程中的局限性,以多周期的再制造闭环供应链网络为研究对象,利用均衡理论和变分不等式的方法构建了基于再制造的多周期闭环供应链网络均衡模型,得到了制造商和零售商及整个供应链网络的均衡条件及其经济解释,并分析了均衡解的唯一性条件。针对所建立的模型,利用Euler算法进行了算例分析,说明了潜在市场份额对供应链成员决策的影响。     

Routing of Railway Carriages

In the context of organizing timetables for railway companies the following railway carriage routing problem occurs. Given a timetable containing rail links with departure and destination times/stations and the composition of the trains, find a routing of railway carriages such that the required carriages are always available when a train departs. The problem is formulated as an integer multi-commodity network flow problem with nonlinear objective function. We will present a local search approach for this NP-hard problem. The approach uses structural properties of the integer multi-commodity network flow formulation of the problem. Computational results for a real world instance are given.     

Fractional multi-commodity flow problem: Duality and optimality conditions

This paper deals with multi-commodity flow problem with fractional objective function. The optimality conditions and the duality concepts of this problem are given. For this aim, the fractional linear programming formulation of this problem is considered and the weak duality, the strong direct duality and the weak complementary slackness theorems are proved applying the traditional duality theory of linear programming problems which is different from same results in Chadha and Chadha (2007) [1]. In addition, a strong (strict) complementary slackness theorem is derived which is firstly presented based on the best of our knowledge. These theorems are transformed in order to find the new reduced costs for fractional multi-commodity flow problem. These parameters can be used to construct some algorithms for considered multi-commodity flow problem in a direct manner. Throughout the paper, the boundedness of the primal feasible set is reduced to a weaker assumption about solvability of primal problem which is another contribution of this paper. Finally, a real world application of the fractional multi-commodity flow problem is presented.     

Development of a new approach for deterministic supply chain network design

This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. The strategic level of supply chain planning and tactical level planning of supply chain are aggregated to propose an integrated model. The model integrates location and capacity choices for suppliers, plants and warehouses selection, product range assignment and production flows. The open-or-close decisions for the facilities are binary decision variables and the production and transportation flow decisions are continuous decision variables. Consequently, this problem is a binary mixed integer linear programming problem. In this paper, a modified version of Benders’ decomposition is proposed to solve the model. The most difficulty associated with the Benders’ decomposition is the solution of master problem, as in many real-life problems the model will be NP-hard and very time consuming. In the proposed procedure, the master problem will be developed using the surrogate constraints. We show that the main constraints of the master problem can be replaced by the strongest surrogate constraint. The generated problem with the strongest surrogate constraint is a valid relaxation of the main problem. Furthermore, a near-optimal initial solution is generated for a reduction in the number of iterations.     

A two-stage stochastic programming framework for transportation planning in disaster response

This study proposes a two-stage stochastic programming model to plan the transportation of vital first-aid commodities to disaster-affected areas during emergency response. A multi-commodity, multi-modal network flow formulation is developed to describe the flow of material over an urban transportation network. Since it is difficult to predict the timing and magnitude of any disaster and its impact on the urban system, resource mobilization is treated in a random manner, and the resource requirements are represented as random variables. Furthermore, uncertainty arising from the vulnerability of the transportation system leads to random arc capacities and supply amounts. Randomness is represented by a finite sample of scenarios for capacity, supply and demand triplet. The two stages are defined with respect to information asymmetry, which discloses uncertainty during the progress of the response. The approach is validated by quantifying the expected value of perfect and stochastic information in problem instances generated out of actual data.     

考虑直销的多期供应链网络均衡模型

研究了直销供应链网络动态均衡模型,分别对制造商、零售商和需求市场的决策者的多期独立决策行为及其相互作用进行了分析,利用变分不等式构建了各层均衡模型以及系统均衡模型,得到了系统达到均衡的条件,给出了具体算例并进行了求解.构建的供应链网络动态均衡模型具有更好的适用性及普遍性,为供应链的各层成员保持供应链的稳定和长期均衡提供决策依据和决策方法.     

基于网络控制的供应链库存系统的稳定性分析

针对一类供应链库存系统,研究了系统的闭环稳定性问题.创新点在于通过引入网络控制的思想,把供应链库存系统建模成网络时滞控制系统.在网络诱导时滞的上下界和丢包率已知的前提下,通过网络控制器的设计,分析了供应链库存系统的稳定性,并利用自由权矩阵和Lyapunov稳定性理论,给出了供应链库存系统渐近稳定的充分条件,并通过数值仿真验证了所提控制方案的可行性和有效性.