一类允许节点失效的多信息流随机流量网络的可靠度研究

This paper studies the performance index that the system probability is not less than the given demand for a stochastic-flow network whtere each arcs and nodes have several capacities and multiple types of commodities transmitted through the same network. One solution procedure is proposed to evaluate the multi-commodity reliability and a simple algorithm is presented in terms of MPs. An illustrative example is given and the difference between multiple types of commodities systems and single commodity systems is discussed.     

Reliability assessment of a multistate freight network for perishable merchandise with multiple suppliers and buyers

This study develops a multistate freight network for single and perishable merchandise to assess the freight performance, where a node denotes a supplier, a distribution centre, or a buyer, while a logistics company providing a freight traffic service is denoted by an edge. For each logistics company, carrying capacity should be multistate since partial capacity may be reserved by some customers. The merchandise may perish or be perished during conveyance because of disadvantageous weather or collision in carrying such that the number of intact cargoes may be insufficient for the buyers. Hence, according to the perspective of supply chain management, the reliability, a probability of the network to successfully deliver the cargoes from the suppliers to the buyers subject to a budget, is proposed to be a performance index, where the suppliers and buyers are not the previous customers. An algorithm in terms of minimal paths to assess the reliability is developed. A fruit logistics case is adopted to explore the managerial implications of the reliability using sensitivity analysis.     

多级多商品流物流网络设计的优化模型与组合模拟退火算法*

以最小化系统内的建设费用、库存费用和运输费用为优化目标,建立可描述一般性带能力约束的多级多商品流物流网络设计问题的优化模型,并根据物流网络设计问题的特点,基于模拟退火算法的思想,设计组合模拟退火算法对模型进行求解。算例的计算结果表明,该优化方法运算快捷,结果正确合理,能为此类物流网络设计问题提供科学的决策依据;通过分析发现,存储费用和运输费用都会影响物流网络系统的总费用,但运输费用对系统总费用的影响程度相对要大得多。     

基于变分不等式的多商品物流网络优化设计

为优化设计多级多商品流的物流网络,按网络状态把物流网络划分为静态网络和动态网络,分析了静态网络的基础设施建设和动态网络的物流活动问题,构建了可描述不同网络阶段的运营成本和建设成本函数,并且考虑了运营过程带来的环境污染问题,构建了治理费用函数。基于以上函数,建立以供给能力为约束条件,以总成本最小为目标的网络设计和重新设计模型,然后将模型转换为变分不等式问题,证明了所设计模型与变分不等式等价。最后通过算例,运用修正投影算法对模型进行数值演算和验证,得到了最优成本下的设施建设方案和物流组织方案。     

A planning model and solution algorithm for multi-trip split-delivery vehicle routing and scheduling problems with time windows

This study proposes a daily vehicle routing model for minimizing the total cost of replenishing inventory within a supply chain. The first major contribution of this research is to allow multiple use of vehicles in a split delivery vehicle routing problem with time windows (SDVRPTW), which is more realistic for various real-life applications. The multi-trip SDVRPTW (MTSDVRPTW) is formulated using the time–space network technique, which provides greater flexibility for formulating the complicated interactions between vehicles and products when multi-trip, split delivery, and delivery time windows are simultaneously considered. The resulting formulation of the MTSDVRPTW can be categorized as an integer multi-commodity network flow problem with side constraints. A two-step solution algorithm is proposed to solve this NP-hard problem, which is the second major contribution of this research. Finally, a real-world scale numerical example is performed to demonstrate and to test the methodology. The results indicate that these vehicle routing problems can be solved effectively and efficiently and that the proposed methodology has great potential for inventory replenishment scheduling where split deliveries and multiple trips for a single vehicle are allowed and time window constraints are imposed.     

Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network

The multi-modal freight transportation network plays an important role in the economic vitality of states, regions, and the broader country. The functionality of this network is threatened by disruptive events that can disable the capacity of the network to enable flows of commodities in portions of nodes and links. This work integrates a multi-commodity network flow formulation with an economic interdependency model to quantify the multi-industry impacts of a disruption in the transportation network to ultimately measure and assess the importance of network components. The framework developed here can be used to measure the efficacy of strategies to reduce network vulnerability from the unique perspective of multi-industry impacts. The framework is illustrated with a case study considering the multi-modal freight transportation network consisting of inland waterways, railways, and interstate highways that connect the state of Oklahoma to surrounding states.     

Optimal Routing Designs in Self-healing Communications Networks

Self-healing communication networks that allow re-routing of demands through switching processes at designated nodes are studied. It is shown how network utilization, demand throughput and reliability of such networks can be studied simultaneously to achieve an optimal design for all three. This is done through a max–min–max multi-commodity network flow formulation of the routing problem in which it is ensured that maximum network throughput is achieved with minimum loss of demands that are blocked due to single switching node failures. It is shown that a node-path linear programming approximation to the multi-commodity network flow formulation solves the problem for medium and large network sizes in moderate computational times.     

Reliability evaluation of a stochastic-flow distribution network with delivery spoilage

From the supply chain management perspective, this paper focuses on evaluating network reliability of a stochastic-flow distribution network (SFDN) under the delivery spoilage consideration. An SFDN is composed of nodes and routes, where each node denotes a supplier, a transfer center, or a market, and each route connects a pair of nodes. Along each route, there is a carrier whose available capacity is stochastic. Moreover, goods may rot or be spoilt during delivery due to traffic accidents, collisions, natural disasters, weather, time, etc., and thus the intact goods may not satisfy the market demand. Network reliability is defined as the probability that the SFDN can satisfy the market demand under the delivery spoilage consideration and the delivery budget constraint, and can be regarded as a performance index for distribution activity in supply chain management. An algorithm is developed in terms of minimal paths to evaluate network reliability. A numerical example is given to illustrate the solution procedure. Then a practical case of fruit distribution is presented to emphasize the management implication of network reliability.     

物流包装租赁系统配送库存路径模型与算法

发展物流包装租赁共享系统是解决落后的一次性包装使用方式的有效手段。为优化物流包装租赁系统中的空包装配送与库存控制这一频繁决策问题,将租赁客户点的需求和物流包装租赁系统的服务中心的库存能力、库存费用、车辆容量、单位运费等因素引入模型,建立了总成本费用最小的物流包装租赁共享系统的空包装配送库存路径集成优化模型。针对稍小和稍大规模算例,对利用CPLEX优化软件和带精英保留的改进遗传算法进行了求解比较分析,结果表明：改进遗传算法对稍大规模算例求解的结果虽然稍差,但求解时间大大缩短,这说明了启发式算法对大规模的实际问题是有效的。该模型和算法可为物流包装租赁企业的空包装配送和库存控制的集成优化决策提供参考。     

非轴辐式快递网络的航线规划研究

快递服务要求在一个时间限制内（24小时、48小时等）将货物从起点运送到目的地,由于对时间的严格要求,长距离的运输一般由飞机完成。回顾了快递航线网络规划的经典模型,并研究了多货物流的非轴辐式快递网络,建立数学模型,分别提出了基于NLP模型和改进的ESSND模型的两种求解方法。最后,设计算例,详细说明了这两类方法的使用,并得出结论改进的ESSND模型能够获得接近最优的结果。     

Measure the quality level for a supplier-demand system by a multicommodity stochastic-flow network

From the point of view of quality management, it is important to meet the customer's demand. The probability that the system can satisfy the customer's demand is an important performance index, and can be used to measure the quality level of the system. In this paper, we use a multicommodity stochastic-flow network to describe the relationship between the supplier and the customer. Each node as well as each arc has several possible capacities and may fail. The network allows multiple types of commodities to be transmitted from the source to the sink. Given the demand for each commodity at the sink, evaluation of the probability that the system meets the demands is performed. Such a probability, named the system reliability, is a performance index of quality level. At first, a simple algorithm is proposed to generate all lower boundary points for the demand, and the system reliability can be calculated in terms of such points. The computational complexity of the proposed algorithm is polynomial time in number of arcs, nodes and minimal paths.     

Load-dependent and precedence-based models for pickup and delivery problems

We address the one-to-one multi-commodity pickup and delivery traveling salesman problem (m-PDTSP) which is a generalization of the TSP and arises in several transportation and logistics applications. The objective is to find a minimum-cost directed Hamiltonian path which starts and ends at given depot nodes and such that the demand of each given commodity is transported from the associated source to its destination and the vehicle capacity is never exceeded. In contrast, the many-to-many one-commodity pickup and delivery traveling salesman problem (1-PDTSP) just considers a single commodity and each node can be a source or target for units of this commodity. We show that the m-PDTSP is equivalent to the 1-PDTSP with additional precedence constraints defined by the source–destination pairs for each commodity and explore several models based on this equivalence. In particular, we consider layered graph models for the capacity constraints and introduce new valid inequalities for the precedence relations. Especially for tightly capacitated instances with a large number of commodities our branch-and-cut algorithms outperform the existing approaches. For the uncapacitated m-PDTSP (which is known as the sequential ordering problem) we are able to solve to optimality several open instances from the TSPLIB and SOPLIB.     

Assessment of system reliability for a stochastic-flow distribution network with the spoilage property

In supply chain management, satisfying customer demand is the most concerned for the manager. However, the goods may rot or be spoilt during delivery owing to natural disasters, inclement weather, traffic accidents, collisions, and so on, such that the intact goods may not meet market demand. This paper concentrates on a stochastic-flow distribution network (SFDN), in which a node denotes a supplier, a transfer station, or a market, while a route denotes a carrier providing the delivery service for a pair of nodes. The available capacity of the carrier is stochastic because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the system reliability, the probability that the SFDN can satisfy the market demand with the spoilage rate under the budget constraint from multiple suppliers to the customer. An algorithm is developed in terms of minimal paths to evaluate the system reliability along with a numerical example to illustrate the solution procedure. A practical case of fruit distribution is presented accordingly to emphasise the management implication of the system reliability.     

基于可靠连通支配集的高效虚拟骨干网构建算法

在概率性无线传感器网络模型中,提出了一种基于可靠连通支配集的高效虚拟骨干网构建算法(EVBP-RCDS).在删除网络中低于节点递交概率阈值的连接基础上,通过递减节点递交概率和对比节点递交概率有效度(EDDP)之和构建出所提出的可靠连通支配集;非支配节点选取与其相邻的拥有最高递交概率的支配节点传输数据.仿真实验表明:与现有文献中的两种算法相比,EVBP-RCDS算法能高效扩展网络生存时间和降低网络延迟.     

A computational study for common network design in multi-commodity supply chains

In this paper, we study a supply chain network design problem which consists of one external supplier, a set of potential distribution centers, and a set of retailers, each of which is faced with uncertain demands for multiple commodities. The demand of each retailer is fulfilled by a single distribution center for all commodities. The goal is to minimize the system-wide cost including location, transportation, and inventory costs. We propose a general nonlinear integer programming model for the problem and present a cutting plane approach based on polymatroid inequalities to solve the model. Randomly generated instances for two special cases of our model, i.e., the single-sourcing UPL&TAP and the single-sourcing multi-commodity location-inventory model, are provided to test our algorithm. Computational results show that the proposed algorithm can solve moderate-sized problem instances efficiently.     

A method to evaluate routing policy through p minimal paths for stochastic case

In this paper, a stochastic-flow network is presented to model a computer network in which each arc has various possible capacities and may fail. In order to shorten the transmission time, the transmission protocol allowing the data to be sent through multiple minimal paths simultaneously is utilized for the computer network. However, the minimum transmission time to send a given amount of data is not fixed due to the property of stochastic capacity. Accordingly, the first addressed issue is to evaluate the probability that the network is able to send the data within a time constraint by adopting the transmission protocol. Such a probability is named as transmission reliability that is regarded as a performance indicator to measure the QoS for a computer network. Without knowing all minimal paths in advance, an efficient solution procedure is proposed to calculate transmission reliability. The experimental results of 35 random networks show that the proposed algorithm can be executed efficiently. Moreover, in order to increase transmission reliability, the network administrator decides the routing policy to designate the first and the second priority p minimal paths. The second addressed issue is to evaluate transmission reliability associated with the routing policy. A sort criterion is subsequently presented to find an ideal routing policy.     

An intelligent logistics support system for enhancing the airfreight forwarding business

Abstract: Recent research related to the aircraft container loading and scheduling problem for airfreight forwarding business has seen significant advances in terms of load plan optimization, taking into account the cost and volume of packed boxes. In today's competitive industrial environment, it is essential that freight forwarders are able to collaborate with carriers (airline companies) to achieve the best possible selection of logistics workflow. However, study of contemporary research publications indicates that there is a dearth of articles related to the design and implementation of an intelligent logistics system to support decision‐making on carrier selection, aircraft container loading plans as well as carrier benchmarking. This paper presents an intelligent logistics support system (ILSS) which is able to provide expert advice related to the airfreight forwarding business, enhancing the logistics operations in relevant activities within the value chain of tasks. ILSS comprises a heuristics‐based intelligent expert system which supports carrier searching and cargo trading planning as well as load plan generation. The proposed approach is meant to enhance various operations in the airfreight forwarding business, adopting computational intelligence technologies such as rule‐based reasoning to provide domain advice and heuristics to support the generation of load plans. After potential outcomes are generated by the heuristics‐based intelligent expert system, a neural network engine is applied to support prediction of unexpected events. To validate the viability of this approach, a production system using the ILSS has been developed and subsequently applied in an emulated airfreight forwarding environment. The application results indicate that the operation time from searching for potential carriers to the execution of the order is greatly reduced. In this paper, details related to the structure, design and implementation of the ILSS are also covered with the inclusion of the actual program codes for building the prototype.     

Extend the quickest path problem to the system reliability evaluation for a stochastic-flow network

From the point of view of quality management, it is an important issue to reduce the transmission time in the network. The quickest path problem is to find the path in the network to send a given amount of data from the source to the sink such that the transmission time is minimized. Traditionally, this problem assumed that the capacity of each arc in the network is deterministic. However, the capacity of each arc is stochastic due to failure, maintenance, etc. in many real-life networks. This paper proposes a simple algorithm to evaluate the probability that d units of data can be sent from the source to the sink through the stochastic-flow network within T units of time. Such a probability is called the system reliability. The proposed algorithm firstly generates all lower boundary points for (d,T) and the system reliability can then be computed in terms of such points.Scope and purposeThe shortest path problem is a well-known problem in operations research, computer science, etc. Chen and Chin have proposed a variant of the shortest path problem, termed the quickest path problem. It is to find a path in the network to send a given amount of data from the source to the sink with minimum transmission time. More specifically, the capacity of each arc in the network is assumed to be deterministic. However, in many real-life networks such as computer systems, telecommunication systems, etc., the capacity of each arc is stochastic due to failure, maintenance, etc. Such a network is named a stochastic-flow network. Hence, the minimum transmission time is not a fixed number. This paper proposes a simple algorithm to evaluate the probability that the specified amount of data can be sent from the source to the sink through the network within a given time. Such a probability is called the system reliability.     

Cooperation and profit allocation in two-echelon logistics joint distribution network optimization

Collaborative two-echelon logistics joint distribution network can be organized through a negotiation process via logistics service providers or participants existing in the logistics system, which can effectively reduce the crisscross transportation phenomenon and improve the efficiency of the urban freight transportation system. This study establishes a linear optimization model to minimize the total cost of two-echelon logistics joint distribution network. An improved ant colony optimization algorithm integrated with genetic algorithm is presented to serve customer clustering units and resolve the model formulation by assigning logistics facilities. A two-dimensional colony encoding method is adopted to generate the initial ant colonies. Improved ant colony optimization combines the merits of ant colony optimization algorithm and genetic algorithm with both global and local search capabilities. Finally, an improved Shapley value model based on cooperative game theory and a cooperative mechanism strategy are presented to obtain the optimal profit allocation scheme and sequential coalitions respectively in two-echelon logistics joint distribution network. An empirical study in Guiyang City, China, reveals that the improved ant colony optimization algorithm is superior to the other three methods in terms of the total cost. The improved Shapley value model and monotonic path selection strategy are applied to calculate the best sequential coalition selection strategy. The proposed cooperation and profit allocation approaches provide an effective paradigm for logistics companies to share benefit, achieve win–win situations through the horizontal cooperation, and improve the negotiation power for logistics network optimization.     

Transmission reliability of k minimal paths within time threshold

The quickest path problem involving two attributes, the capacity and the lead time, is to find a single path with minimum transmission time. The capacity of each arc is assumed to be deterministic in this problem. However, in many practical networks such as computer networks, telecommunication networks, and logistics networks, each arc is multistate due to failure, maintenance, etc. Such a network is named a multistate flow network. Hence, both the transmission time to deliver data through a minimal path and the minimum transmission time through a multistate flow network are not fixed. In order to reduce the transmission time, the data can be transmitted through k minimal paths simultaneously. The purpose of this paper is to evaluate the probability that d units of data can be transmitted through k minimal paths within time threshold T. Such a probability is called the transmission reliability. A simple algorithm is proposed to generate all lower boundary points for (d, T), the minimal system states satisfying the demand within time threshold. The transmission reliability can be subsequently computed in terms of such points. Another algorithm is further proposed to find the optimal combination of k minimal paths with highest transmission reliability.