军事物流系统中定位-运输路线安排模型及算法

考虑到战时物资需求的紧迫性和保障资源的有限性,从决策者的角度出发,以军事物流系统总体供应时间最短为目标,构建了两级军事配送网络的定位-运输路线安排模型,并给出一种启发式算法.算法分为两个阶段,首先利用蚁群算法和线性规划的方法解决运输路线安排问题,然后运用贪婪搜索算法解决军事物流配送中心选址问题.最终,将两种算法结合起来进行逐步搜索,从而得到模型的解,并运用实例说明了算法的有效性和可行性.     

应急物资联合配送决策研究

救援物资的高效投放是应急物流的关键活动之一。考虑到灾后救援车辆短缺,分配时受灾群众产生非理性心理,以及灾后道路状况对军、地救灾车辆速度产生影响等因素,本文从军民融合的角度出发,根据军地运输车辆特点,设计科学合理的车辆分配方案与运输路线。论文研究构建了基于车辆分配公平性和应急配送及时性的“分配-运输”集成决策模型,设计改进后的NSGA-Ⅱ算法进行求解,最后通过算例验证本算法的有效性和合理性,并通过调节军民运输车辆数,找到应急救援过程中的最佳军、地车辆比例,从而为灾后各灾备中心的车辆调度决策提供参考。     

Optimization Models for Forest Road Upgrade Planning

Road blocking due to thawing or heavy rains annually contribute to a considerable loss in Swedish forestry. Companies are forced to build up large stocks of raw material (saw and pulp logs) in order to secure a continuous supply when access to the road network is uncertain. Storage outdoors leads to quality deterioration and monetary losses. Other related costs due to road blocking are road damage and longer haulage distances. One approach to reduce the losses due to road blocks is to upgrade the road network to a standard that guarantees accessibility. We consider the road upgrade problem from the perspective of Swedish forest companies with a planning horizon of about one decade. The objective is to minimize the combined upgrade and transportation costs. We present two mixed integer programming models, which are uncapacitated fixed charge network flow problems including multiple assortments, several time periods and a set of road classes. One model is based on arc flows and one on route flows. For a typical planning instance, the models become large and we propose how to improve solution performance through model strengthening. The models are tested in a case study for a major Swedish forest company.      

产业转移下的海上丝绸之路沿线集装箱港口的投资决策研究

在产业转移背景下,考虑港口服务货运需求与刺激货运需求的双重功效,研究海上丝绸之路沿线产业承接地的港口投资建设问题。首先,在现实交通运输网络中加入虚拟链接构建超级网络,用以刻画制造业的转移、生产和运输过程。其次,建立制造业承接地港口投资决策优化模型,用运输阻抗、地价和工资三个内生变量描述港口投资、产业转移与区域经济之间均衡关系。模型以产业承接地港口收益最大为目标,确定承接地港口的投资规模及费率水平。最后,以斯里兰卡的科伦坡口为例进行数值分析,计算海上丝绸之路沿线港口需求与供给间正向反馈的数量关系及上确界,为优化沿线港口投资实现投资利益最大化提供依据。     

产业转移下的海上丝绸之路沿线集装箱港口的投资决策研究

在产业转移背景下,考虑港口服务货运需求与刺激货运需求的双重功效,研究海上丝绸之路沿线产业承接地的港口投资建设问题。首先,在现实交通运输网络中加入虚拟链接构建超级网络,用以刻画制造业的转移、生产和运输过程。其次,建立制造业承接地港口投资决策优化模型,用运输阻抗、地价和工资三个内生变量描述港口投资、产业转移与区域经济之间均衡关系。模型以产业承接地港口收益最大为目标,确定承接地港口的投资规模及费率水平。最后,以斯里兰卡的科伦港口为例进行数值分析,计算海上丝绸之路沿线港口需求与供给间正向反馈的数量关系及上界,为优化沿线港口投资实现投资利益最大化提供依据。     

Environmentally conscious optimization of supply chain networks

The optimization of supply chain structures considering both economic and environmental performances is nowadays an important research topic. However, enterprises are commonly faced with the competing issues of reduced cost, improved customer service and increased environmental factors as a multi-faceted trade-off problem when designing supply chains. Hence, this paper proposes an environmentally conscious optimization model of a supply chain network with a broader and more comprehensive objective function that considers not just the transportation costs, but also the costs for the amount of greenhouse gas emissions, fuel consumption, transportation times, noise and road roughness. The paper sheds light on the trade-offs between various parameters such as vehicle speed, fuel, time, emissions, noise and their total cost, and offers managerial insights on economies of environmentally conscious supply chain optimization. An integer non-linear programming model is developed to help decision makers find the optimal solution under mentioned considerations. The proposed model is validated through the solution of an example, where its applicability to supply chain problems is demonstrated for managerial insights.     

The structure of branched transportation networks

The transportation problem can be formalized as the problem of finding the optimal paths to transport a measure μ ⁺ onto a measure μ ⁻ with the same mass. In contrast with the Monge–Kantorovich formalization, recent approaches model the branched structure of such supply networks by an energy functional whose essential feature is to favor wide roads. Given a flow s in a road or a tube or a wire, the transportation cost per unit length is supposed to be proportional to s ^α with 0 < α < 1. For the Monge–Kantorovich energy α = 1 so that it is equivalent to have two roads with flow 1/2 or a larger one with flow 1. If instead 0 < α < 1, a road with flow is preferable to two individual roads s ₁ and s ₂ because . Thus, this very simple model intuitively leads to branched transportation structures. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electric power supply systems and in natural objects like the blood vessels or the trees. When such structures can irrigate a whole bounded open set of . The aim of this paper is to give a mathematical proof of several structure and regularity properties empirically observed in transportation networks. It is first proven that optimal transportation networks have a tree structure and can be monotonically approximated by finite graphs. An interior regularity result is then proven according to which an optimal network is a finite graph away from the irrigated measure. It is also proven that the branching number of optimal networks has everywhere a universal explicit bound. These results answer questions raised in two recent papers by Xia.     

Integrated Production and Distribution Planning for Södra Cell AB

In this paper we consider integrated planning of transportation of raw material, production and distribution of products of the supply chain at Södra Cell AB, a major European pulp mill company. The strategic planning period is one year. Decisions included in the planning are transportation of raw materials from harvest areas to pulp mills, production mix and contents at pulp mills, distribution of pulp products from mills to customer via terminals or directly and selection of potential orders and their levels at customers. Distribution is carried out by three different transportation modes; vessels, trains and trucks. We propose a mathematical model for the entire supply chain which includes a large number of continuous variables and a set of binary variables to reflect decisions about product mix and order selection at customers. Five different alternatives regarding production mix in a case study carried out at Södra Cell are analyzed and evaluated. Each alternative describes which products will be produced at which pulp mills.     

Profit oriented supply chain network optimization

This paper proposes a novel mixed integer linear programming model to solve a supply chain network design problem. The proposed model deals with major issues for supply chains; product quality and cost. These issues are usually solved separately, but in this paper, we investigate effects of product quality on supply chain design and transportation flow. A trade-off between raw material quality, its purchasing and reprocessing costs was considered. Assuming decision maker (DM) wishes to work with a supplier which serves a low quality raw material; this raw material should be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material should be chosen but at this time the DM has to face a high purchasing cost. A supply chain network which consists of multiple suppliers, manufacturers, distribution centers and retailers is tried to be designed to accomplish aforementioned above trade-offs. The paper examines and discusses the relationship between product quality and supply chain design and offers several managerial insights.     

A Hybrid Taguchi–Immune approach to optimize an integrated supply chain design problem with multiple shipping

Supply chain network design is considered a strategic decision level problem that provides an optimal platform for the effective and efficient supply chain management. In this research, we have mathematically modeled an integrated supply chain design. To ensure high customer service levels, we propose the inclusion of multiple shipping/transportation options and distributed customer demands with fixed lead times into the supply chain distribution framework and formulated an integer-programming model for the five-tier supply chain design problem considered. The problem has been made additionally complex by including realistic assumptions of nonlinear transportation and inventory holding costs and the presence of economies of scale. In the light of aforementioned facts, this research proposes a novel solution methodology that amalgamates the features of Taguchi technique with Artificial Immune System (AIS) for the optimum or near optimum resolution of the problem at hand. The performance of the proposed solution methodology has been benchmarked against a set of test instances and the obtained results are compared against those obtained by Genetic Algorithm (GA), Hybrid Taguchi–Genetic Algorithm (HTGA) and AIS. Simulation results indicate that the proposed approach can not only search for optimal/near optimal solutions in large search spaces but also has good repeatability and convergence characteristics, thereby proving its superiority.     

Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer

This study applies fuzzy sets to integrate the supply chain network of an edible vegetable oils manufacturer. The proposed fuzzy multi-objective linear programming model attempts to simultaneously minimize the total transportation costs. The first part of the total transportation costs is between suppliers and silos; and rest one is between manufacturer and warehouses. The approach incorporates all operating realities and actual flow patterns at production/distribution network with reference to demands of warehouses, capacities of tin and pet packaging lines. The model has been formulated as a multi objective linear programming model where data are modeled by triangular fuzzy numbers. Finally, the developed fuzzy model is applied for the case study, compiled the results and discussed.     

Spatial price equilibrium,distribution center location and successive over-relaxation

A spatial price equilibrium problem is modeled which allows piecewise linear convex flow costs, and a capacity limit on the trade flow between each supply/demand pair of regions. Alternatively, the model determines the locations of intermediate distribution centers in a market economy composed of separate regions, each with approximately linear supply and demand functions. Equilibrium prices, regional supply and demand quantities, and commodity flows are determined endogenously. The model has a quadratic programming formulation which is then reduced by exploiting the structure. The reduced model is particularly well suited to solution using successive over-relaxation.     

基于CVaR的危险品公铁联运路径选择研究

公铁联运在危险品的多式联运中扮演着重要角色,为了降低危险品公铁联运风险,提高危险品公铁联运的安全性,危险品公铁联运的路径选择至关重要。本文运用条件风险价值(CVaR)理论,在对危险品公铁联运网络进行变形的基础上构建了考虑决策者风险规避程度的危险品公铁联运路径选择模型,设计了求解该模型的算法,并进行了算例分析。研究结果表明:通过该模型及其算法,可根据决策者对所需运输的危险品的运输风险规避程度,在危险品公铁联运网络中快速地选出使危险品公铁联运风险最小的运输路径和运输方式;决策者的风险规避程度会对危险品公铁联运过程中的运输路径和运输方式的选择产生重要影响。     

A kind of stochastic duel model for guerrilla war

This paper discusses a stochastic duel model between two forces. On one side are the guerrilla (or terrorists), and on the other an organized force of some sort. The model is called guerrilla war. The guerrilla side has a number of advantages such as choice of location and time of engagement, concealment by topography, observation of the intended target, and line of fire. We represent these advantages in what we believe is a realistic scenario of a duel between the guerrilla force and the organized force. By the four suppositions coinciding with the practical duel background, the paper deduces the formulas for calculating the winning probabilities for the both sides.     

An analytical method for cost analysis in multi-stage supply chains: A stochastic network model approach

This paper studies the cost distribution characteristics in multi-stage supply chain networks. Based on the graphical evaluation and review technique, we propose a novel stochastic network mathematical model for cost distribution analysis in multi-stage supply chain networks. Further, to investigate the effects of cost components, including the procurement costs, inventory costs, shortage costs, production costs and transportation costs of supply chain members, on the total supply chain operation cost, we propose the concept of cost sensitivity and provide corresponding algorithms based on the proposed stochastic network model. Then the model is extended to analyze the cost performance of supply chain robustness under different order compensation ability scenarios and the corresponding algorithms are developed. Simulation experiment shows the effectiveness and flexibility of the proposed model, and also promotes a better understanding of the model approach and its managerial implications in cost management of supply chains.     

军需物资调集规划问题的研究

以军需物资调集为背景 ,在系统分析的基础上建立了全局优化问题的数学规划模型 ,并对模型求解进行了研究 ,提出两阶段规划算法 .仿真计算结果表明所建模型的有效性     

An N-path user equilibrium for transportation networks

The traditional trip-based approach to transportation modeling has been employed for the past decade. The last step of the trip-based modeling approach is traffic assignment, which has been typically formulated as a user equilibrium (UE) problem. In the conventional perspective, the definition of UE traffic assignment is the condition that no road user can unilaterally change routes to reduce their travel time. An equivalent definition is that the travel times of all the used paths between any given origin–destination pair are equal and less than those of the unused paths. The underlying assumption of the UE definition is that road users have full information on the available transportation paths and can potentially use any path if the currently used path is overly congested. However, a more practical scenario is that each road user has a limited path set within which she/he can choose routes from. In this new scenario, we call the resulting user equilibrium an N-path user equilibrium (NPUE), in which each road user has only N paths to select from when making route choices in the network. We introduce a new formulation of the NPUE and derive optimality conditions based on this formulation. Different from traditional modeling framework, the constraints of the proposed model are of linear form, which makes it possible to solve the problem with conventional convex programming techniques. We also show that the traditional UE is a special case of an NPUE and prove the uniqueness of the resulting flow pattern of the NPUE. To efficiently solve this problem, we devise path-based and link-based solution algorithms. The proposed solution algorithms are empirically applied to networks of various sizes to examine the impact of constrained user path sets. Numerical results demonstrate that NPUE results can differ significantly from UE results depending on the number of paths available to road users. In addition, we observed an interesting phenomenon, where increasing the number of paths available to road users can sometimes decrease the overall system performance due to their selfish routing behaviors. This paradox demonstrates that network information should be provided with caution, as such information can do more harm than good in certain transportation systems.     

A dynamic inventory model with supplier selection in a serial supply chain structure

Considering the inherent connection between supplier selection and inventory management in supply chain networks, this article presents a multi-period inventory lot-sizing model for a single product in a serial supply chain, where raw materials are purchased from multiple suppliers at the first stage and external demand occurs at the last stage. The demand is known and may change from period to period. The stages of this production–distribution serial structure correspond to inventory locations. The first two stages stand for storage areas for raw materials and finished products in a manufacturing facility, and the remaining stages symbolize distribution centers or warehouses that take the product closer to customers. The problem is modeled as a time-expanded transshipment network, which is defined by the nodes and arcs that can be reached by feasible material flows. A mixed integer nonlinear programming model is developed to determine an optimal inventory policy that coordinates the transfer of materials between consecutive stages of the supply chain from period to period while properly placing purchasing orders to selected suppliers and satisfying customer demand on time. The proposed model minimizes the total variable cost, including purchasing, production, inventory, and transportation costs. The model can be linearized for certain types of cost structures. In addition, two continuous and concave approximations of the transportation cost function are provided to simplify the model and reduce its computational time.     

基于道路堵塞及顾客时间要求的快件配送最优路径选择

针对道路堵塞如节假日导致的临时最短配送路径失效的问题,提出配送网络最优路径选择模型,并设计了求解快递配送网络关键边和最优路径的算法。首先,计算出整个网络的关键边,掌握配送网络特征;其次,考虑顾客时间要求,研究不完全信息(中断无法提前预知,只有到达中断边的起点处才可知)下的最优路径,根据最短路径上各边新的特点,计算出每条边中断后对应的一组备用路径,再选择运输时间小于或等于顾客可等待时间的路径为有效路径,考虑道路堵塞情况,从有效路径中选择最优路径;最后,结合配送网络的实际情况对最优路径进行了算例分析。     

Concurrent optimization in designing for logistics support

Concurrent Engineering has always been an important field within military industry and is gaining recognition within commercial industry as well. Studies have suggested that long-range research efforts need to be directed to the area of integrated logistics. In order to satisfy the overall logistics objectives, product designs must incorporate consideration of the impact that design decisions have on operations, maintenance, transportation and supply. This paper presents a model that carries out a concurrent optimization of a product design and its associated manufacturing and logistics support systems. We offer this model as a framework for decision support of concurrent engineering activities.