Dynamic variations in pickers’ capability are crucial for task assignment efficiency, yet are often overlooked in research due to the focus on system-level optimization and the complexity of modeling human variability. This paper addresses the problem of order fulfillment task assignment considering the pickers’ dynamic capability. A unique feature of the proposed approach is the integration of a data-driven model for characterizing capability with a mixed integer programming optimization model for online task assignment. To solve the model and leverage the pickers’ dynamic capability, we developed a variable time window algorithm based on the proportion of available pickers. Numerical experiments are conducted using data obtained from a warehouse located in Southwest China. The results indicate that our approach significantly improves the accuracy of characterizing pickers’ capability. Additionally, our model modestly reduces total execution time and achieves a notable improvement of over 20% in labor equilibrium. With the help of our model, the warehouse manager can clearly assess the dynamic variations of pickers’ capability and make informed task assignment decisions, ensuring efficient and equitable labor utilization.

To overcome the difficulties of establishing rigid connections between segments of steel truss suspension bridges, in this study a shape stiffness connection (SFRC) method is proposed and an attempt is made to apply it to the Kahaluo Jinsha River Bridge (a steel truss suspension bridge in Sichuan, China). First, the basic principles using the unstressed state approach are elucidated and the proposed method is validated by leveraging the deflection theory. Insights from practical projects substantiate the accuracy of the proposed method. The influence of secondary dead loads on the rigid connection timing during the lifting process is investigated. The results show that this method does not affect the internal force state of the structure at completion stage, and ensures the rigid connection forces are consistently below 200 kN, thereby reducing the difficulties in forming rigid connections. In addition, the optimal timing for rigid connections advances with the increase of the secondary dead loads. A functional relationship between the secondary dead load proportion and the percentage of lifted segments to the total girder segments after completing the rigid connection is established. Through applications to additional real-world bridges, the reliability of the predictive equation is further confirmed. These findings highlight the potential advantages of the SFRC method in practical engineering projects.

The robotic mobile fulfillment system (RMFS), with wide application in warehousing and logistics, requires many robots powered by electricity, which significantly impacts energy consumption. This paper investigates the energy consumption in the RMFS under a classic e-business environment, which classifies the orders into regular orders and expedited orders. We evaluate the impact of three dynamic priority policies (the earliest deadline first policy, waiting time-dependent policy, and weighted waiting time first policy) on throughput time and energy consumption. This paper proposes multi-class semi-open queuing network models (SOQN) with dynamic priority policies to investigate energy consumption. We validate the accuracy of the analytical models by simulation models. This paper makes the following contributions: (1) In methodology, we propose new methods to solve the SOQN with dynamic priority policies. (2) In operational planning and control, we are among the earliest to investigate the impact of dynamic priority policies on order throughput time and energy consumption in an RMFS. (3) In design optimization, we propose a decision tool to optimize the robot number for realizing the required throughput time with minimal energy consumption. Our model can also decide the optimal warehouse shape to minimize energy consumption. (4) In system analysis, we estimate the energy consumption per transaction in an RMFS, providing logistics managers insights into energy saving of warehouses.

Accurate data collection in manual warehouses faces significant challenges due to the reliance on singular information collection method and the operators' flexibility, which impedes data-driven, intelligent decisionmaking in warehouse operations. This paper addresses this problem to construct the data chain using indoor positioning technology (DCC-IPS). A unique feature of the proposed approach is the integration of the operators' positioning data with the layout, operations, and tasks in the warehouse, facilitating a deep fusion of new external data and internal business data. Experiments conducted at Southwest Jiaotong University's laboratory have demonstrated that the DCC-IPS achieves a matching accuracy exceeding 80%. Compared to traditional scanning with PDA, DCC-IPS reduces the delay in operation recognition by 20 s in the experimental scenario. Furthermore, by utilizing the data chain for evaluating operators' capability and optimizing task assignments, our numerical experiments showed a 22.13% increase in efficiency over random assignments. These results highlight the accuracy and effectiveness of DCC-IPS in enhancing operational efficiency in warehouses.

As an efficient logistics mode, multimodal transport can effectively integrate the advantages of various transportation modes and reduce energy consumption and carbon emissions. Aiming at the low-carbon multimodal transport path optimization problem, this paper provides a hybrid optimization method combining genetic algorithm and particle swarm optimization algorithm, establishes a multi-objective optimization model considering transport time, cost and carbon emission, and designs a PSO-GA hybrid algorithm to realize the comprehensive optimization of multimodal transport path. Finally, a numerical example is given to verify the effectiveness and feasibility of the proposed method. The results show that the PSO-GA hybrid algorithm can effectively reduce the transportation cost and carbon emissions of multimodal transportation while ensuring transportation efficiency, and provide theoretical support and practical guidance for the low-carbon development of China’s transportation industry, which will help China set a model of low-carbon development in the field of global transportation and make positive contributions to the global response to climate change.

通过构建交通运输类虚拟仿真实验教学体系,着重破解在实验教学中存在的虚拟仿真实验教学资源共享不充分,实验教学与行业产业需求匹配脱节,缺乏多岗位协同和多场景模拟以及实验内容与现有教学环节融合度不高等问题.聚焦高铁列车调度指挥、库存管理与自动化仓储、城市轨道交通调度指挥等关键问题,以点带面,重点打造了系列国家级、省级高阶性虚拟仿真实验教学课程,紧密融合交通运输类专业课程体系,构建符合交通运输类的人才培养模式,实现贯通式人才培养过程,提出并实践了4个"二一"虚拟仿真实验教学方法,为虚拟仿真实验课程的教学改革与实践提供了支撑.

This paper evaluates the performance of a robotic mobile fulfillment system (RMFS) with multiple picking stations under a zoning policy. Focusing on a single picking process performed by robot, we develop an expected travel time model for the robot considering a constant velocity, and evaluate the system performance according to the travel time. Compared with the data of the actual RMF system from FAW Logistics Co., Ltd, the model developed in this study has high accuracy and can be used to rapidly evaluate the performance of RMFS with different layouts. In addition, by the numerical experiments, the effect of the number of horizontal aisles and two zoning policies on system performance is analyzed. The results show the following: (1) With the initial total number of storage locations determined, when picking efficiency and space utilization are taken as indexes for planning and designing, the optimal scheme can be obtained more directly by focusing on the effect of the number of horizontal aisles on the expected travel time. (2) Under the relevant assumptions and system characteristics proposed herein, when the expected travel time is taken as the index, it is always better to store A-class goods in the center of the pod storage area.

In this paper, we study a multi-objective supply, production and distribution planning problem (MSPDP) originated from a dairy company in China, where three echelons of supply chain including customers, pastures, and factories are considered. In practice, the company endeavors to utilize raw milk and production capacity simultaneously to manufacture dairy products required by customers from all over the country, and then try to select a suitable mode of transportation to distribute the finished products to each customer. The whole process is a complex upstream-and-downstream coordination system of the supply chain taking multitudinous constraints into consideration. A novel mixed integer programming (MIP) model is proposed to address this problem. Except for the usual characteristics in the dairy industry, such as order fulfillment, cost, equilibrium in production, multi-product, multi-periods, multi-factories, multi-pastures, production lot size, transportation mode, and so on, we also consider a special constraint that raw milk is graded by quality and can be demoted to use, which makes our model different from other studies in the dairy industry. Moreover, the performance of the proposed model is evaluated by several actual instances from the dairy company, and the results prove that our model meet the requirement of industrial application.

面向新时代物流人才需求,首先提出了物流专业产教融合人才培养体系.然后,提出了物流专业产教融合平台的实施模型和创新机制,该平台具有交流平台、资源共享平台、人才培养平台、课程创新平台、教师职业发展平台、科研协同创新平台和就业创业平台的集成功能.最后,介绍了西南交通大学依托两个国家实验室正在打造的物流专业产教融合平台,及通过平台实施产教融合人才培养的具体实践.

随着我国智慧物流的快速推进,物流领域"实践领先研究"的倒逼局面已经成为全国各高校物流类人才培养的普遍性问题.鉴于其典型的多学科交叉属性,构建了"实践+创客+竞赛"的物流跨学科创新人才培养模式,提出了支撑双创人才培养的改革思路与措施,为物流工程专业创新型人才培养提供一定的参考.

With the further development of manufacturing servitization, the supply chain established by enterprises has gradually evolved into a product service supply chain. The introduction of service flow has made supply chain management more complicated. In this paper, we build a product service supply chain network composed of raw material suppliers, service providers, manufacturing integrators, and customers. The equilibrium model for decision-makers at all levels is established by variational inequality. In particular, we emphasize the impact of product and service capacity constraints and changes in the product service integration ratio on network equilibrium. The results show that, while capacity constraints on production tend to stabilize and unify the market price, service-related capacity constraints polarize the customer pay price. That is to say, product capability constraints limit the quality of product service systems, while service capability constraints limit the types of product service systems. Furthermore, the introduction of service flow and integration with products creates a more closely networked relationship between the upper and lower layers of the product service supply chain, and an increase in the service proportion will increase the network equilibrium profit.

The rack-moving mobile robot (RMMR) system is a special parts-to-picker automated warehousing system that uses hundreds of rack-moving machines to accomplish the repetitive tasks of storing and retrieving parts by lifting and transporting unit racks autonomously. This paper investigates the operation cycle of the rack-moving machine for storage and retrieval from the perspective of the lane depth, especially exploring the particularity of the RMMR system in multi-deep lanes, and proposes expected travel time models of the rack-moving machine for single- and multi-deep layouts of the RMMR system. To validate the effectiveness of the proposed models, an experimental simulation was conducted with a 1-4-deep layout under six scenarios of different numbers of aisles and layers, and results were compared with results obtained using proposed models. The paper presents useful guidelines for the configuration of the RMMR system layout including the determination of the optimal lane depth.

在线路客流控制中,需同时考虑各个车站控流方案的可执行性与协同性.采用Fisher最优分割法确定合理客流控制时段,基于此建立以乘客总等待时间最少和旅客周转量最大为目标的线路客流协同控制线性规划模型.基于成都地铁2号线AFC数据进行实验,针对协同控流与非协同控流方案,以及不同客流控制时段划分方案下的协同控流方案进行对比实验.算例中:协同控流方案在旅客周转量下降约1.0％的情况下,乘客总等待时间减少约56.7％;基于Fisher最优分割法确定的时段划分方案中协同控流方案在乘客总等待时间方面最优,并具有很好的可执行性.

In responding to the extremely weak global economy after the …nancial crisis in 2008, many industrial nations have been considering or have already implemented negative nominal interest rate policy. This situation raises two important questions for monetary theories: (i) Given the widely held doctrine of the zero lower bound on nominal interest rate, how is a negative interest rate (NIR) policy possible? (ii) Will NIR be e¤ective in stimulating aggregate demand? (iii) Are there any new theoretical issues emerging under NIR policies? This article builds a model to show that (i) money injections can remain e¤ective even when the nominal bank lending rate has reached zero or become negative; (ii) it is a good policy to keep the nominal interest rate as low as possible by purchasing government bonds with money; and (iii) the conventional wisdom on the notion of the liquidity trap and the Fisherian decomposition between the nominal and real interest rate can be invalid.

To ensure the effective use of construction funds and realize the planning of pickup network for the target market, the phased construction of terminal distribution network under different targets was proposed with consideration of the cost constraints. By taking the level of pickup points and requirement type of customers into consideration, the second stage construction plan was designed based on the construction plan at first stage. The two-stage layout optimization model with maximum demand coverage and weighted satisfaction enhancement was thus established. The genetic algorithm was used to solve the optimization problem, which was verified by a case. Also, the influences of the budget allocation on the construction scheme was also analyzed. Results show that if the enterprise's cash flow capacity is limited, it should allocate the budget according to its own emphasis on the development target; if capable, it is recommended to invest as much as possible in the first stage.

Based on linking up logistics service function and the organization of railway freight transportation, the AnyLogic software was applied to simulate and analyze the operation procedure of train container logistics center integrating multi-functions of storage, packing, loading, unloading. The result shows that the average operating time in storage is 103 minutes on the premise of initial parameter setting, and the average outbound interval time is 1.1 minutes. The maximum storage processing capacity occurs when the quantities of forklifts are between 30 and 35. When loading rate is higher than 3 per hour and unloading rate is below 4 per hour, the operating efficiency of logistics center reaches its maximal point.

The split delivery vehicle routing problem (SDVRP) is a variation of the capacitated vehicle routing problem in which some customers may be served by more than one vehicle. We have proposed a particle swarm optimization approach that incorporates a local search to solve the SDVRP. An integer coding method was presented, and a decoding method based on Bellman's equation was modified for the SDVRP. A way to address the differences in the length of the velocity vector, the position vector, the personal best position vector, the local best position vector and the global best position vector was designed. Two groups of local searches for top solutions were incorporated into the algorithm, with the ability to control whether they are executed on a given solution. The algorithm was initially tested using the modified Solomon's instances to verify the parameters used, including the local search probability, the size of the swarm, the velocity equation and the length of the vectors. Extensive computational experiments were carried out on 131 benchmark instances available in the literature. The results obtained were competitive. More precisely, equally good solutions were found in 32 instances, and improved solutions were found in 35 instances, with an average improvement of 0.02% and a maximum improvement of 1.12%.

城市文脉是连接城市传统文化与现代建筑的脉络，是一座文化古城不可或缺的存在，历史悠久的传统街巷则是表征城市文脉的主要载体。本文以都江堰西街为研究对象，对古城镇的传统街巷更新与改造进行探究，以解析其空间特质，诠释文化内涵，为今后传统街巷改造更新提供思路。

The higher education field has always emphasized"deep learning".Based on the theory of deep learning, the idea of the professional talents cultivation in Logistics Management and Engineering Major has been put forward in this paper.The newly proposed "flipped learning"has deepened the concept of"flipping", and ultimately focuses on the promotion of deep learning.According to the deep learning route, the flipped learning model is proposed.Finally, this model is used to carry out the teaching practice.It is aiming to promote students in Logistics Management and Engineering Major to achieve deep learning based on deep learning route.

As a new type of retail business, chain convenience stores meet customers' convenience and quick demand for shopping. However, the store area is small, and the fresh food with short shelf life accounts for a large proportion. It is necessary to implement the low-volume, multi-batch, high-efficiency and low-cost replenishment strategy. Because the sales of fast food, rice balls, and other high-temperature foods are greatly affected by the weather, this paper takes the high-temperature food in chain convenience stores as the research object. The multi-period replenishment model is established with the goal of maximizing profit under the influence of weather factors. Finally, taking, a 7-ELEVEn convenience store as an example, the case studies are analyzed to discuss the replenishment strategies under different weather conditions and different sales periods.