Utilization Of Transport Capacity Research Articles

Joint Optimal Train Rescheduling and Passenger Flow Control for Speed Limit and High-Demand Scenarios of Urban Rail Transits

In the operation of urban rail transits, train delays occur frequently, and emergency management is one of the key factors to ensure the service quality. For speed limit scenarios with high demand, this paper takes the train running in the restricted manual (RM) mode in the speed limit zone as an example and discusses a coping method by jointing train rescheduling and passenger flow control. With the goal of maximizing the number of passengers served and minimizing total train delay, a nonlinear optimization model is constructed by taking the train operation-related requirements and passenger flow control-related indicators as constraints, and the model is reformulated to a mixed-integer programming (MIP) model with quadratic constraints, which can be solved by the Gurobi solver. In order to obtain effective solutions faster, a two-stage approach is discussed, which first obtains a rescheduling timetable and then dynamically adjusts the requirement of boarding equalization to obtain the passenger flow control scheme. The validity of the model and the solution approach are discussed with the help of numerical experiments. The results suggest that the model and solution approach are feasible. When the number of trains is fixed, the reasonable implementation of passenger flow control will help to increase the number of passengers served, and the pursuit of a higher equalization of boarding is not conducive to the number of passengers served and the full utilization of transport capacity. The two-stage approach has certain advantages over the direct computing method. The methods in this paper have a guiding value for emergency decision-making in similar delay scenarios.

Strategic bidding in freight transport using deep reinforcement learning

AbstractThis paper presents a multi-agent reinforcement learning algorithm to represent strategic bidding behavior by carriers and shippers in freight transport markets. We investigate whether feasible market equilibriums arise without central control or communication between agents. Observed behavior in such environments serves as a stepping stone towards self-organizing logistics systems like the Physical Internet, while also offering valuable insights for the design of contemporary transport brokerage platforms. We model an agent-based environment in which shipper and carrier actively learn bidding strategies using policy gradient methods, posing bid- and ask prices at the individual container level. Both agents aim to learn the best response given the expected behavior of the opposing agent. Inspired by financial markets, a neutral broker allocates jobs based on bid-ask spreads. Our game-theoretical analysis and numerical experiments focus on behavioral insights. To evaluate system performance, we measure adherence to Nash equilibria, fairness of reward division and utilization of transport capacity. We observe good performance both in predictable, deterministic settings ($$\sim $$ ∼ 95% adherence to Nash equilibria) and highly stochastic environments ($$\sim $$ ∼ 85% adherence). Risk-seeking behavior may increase an agent’s reward share, yet overly aggressive strategies destabilize the system. The results suggest a potential for full automation and decentralization of freight transport markets. These insights ease the design of real-world market platforms, suggesting an innate tendency of markets to reach equilibria without behavioral models, information sharing or explicit incentives.

Measuring supply chain performance: the triple E model

PurposeThis work aims to measure the performance of an electric motors supply chain (SC) by using the Triple E performance measurement model to assess three performance dimensions simultaneously: efficiency, efficacy and environmental impact.Design/methodology/approachThis research presents a real case of a Brazilian company as an example for applying the Triple E performance measurement model and the discrete-event simulation to assess the performance of an SC.FindingsPerformance measurements for the three dimensions were the following: (1) for efficiency, a high inventory cost in the SC, driven by the distribution center (DC) (49.7% total cost); an order cycle time operating with an average of 21.7 days and a logistic channel transport capacity of 88%; (2) for efficacy, a service level of 98% for all channels; (3) for environmental impact, the SC emits a total of 395,733 kg of CO2 annually, with the DC and the regional distribution center (RDC2) being the largest emitters.Originality/valueThis work allowed to measure the performance of an SC interface (manufacturing process, a DC and three regional distribution centers). It was possible to measure the inventory holding cost and out-of-stock inventory costs, order cycle time, SC service level, transport capacity utilization and CO2 emissions in the transportation process of each SC stage and the whole SC. This study can be used as a decision support guide for academics and practitioners to measure and improve the SC performance.

Model of Using the Exhaustive Search Algorithm in Solving of Traveling Salesman Problem (TSP) on the Example of the Transport Network Optimization of Primorje-Gorski Kotar County (PGC)

This paper considers and presents a model of the use of an exhaustive search algorithm in solving problems of a salesman on the example of the transportation network optimization of Primorsko Goranska County. By identifying the suboptimal solutions of transportation network, that enable insight into more transportation routes and can be significantly influenced by the reduction of transportation costs and creating increased opportunities for the carrier in the context of flexible designing the structure of the commodity flows, greater utilization of transport capacity, and thus achieve greater profit. In the analyzed example, transportation network of Primorje-Gorski Kotar County (PGC) is divided into two sets (segment): 1) a set of cities (nodes) that are located (placed) on the same traffic direction (transportation route) that represents the optimal transportation route, and 2) a set of cities (nodes) that connect through a variety of transport relationships and that are included in the calculation by using the exhaustive search algorithm. In the example are also defined nodes that are common to both the two sets and that are connecting by the virtual transportation route in the spreadsheet optimization model.

The impact of making vaccines thermostable in Niger's vaccine supply chain

ObjectiveDetermine the effects on the vaccine cold chain of making different types of World Health Organization (WHO) Expanded Program on Immunizations (EPI) vaccines thermostable. MethodsUtilizing a detailed computational, discrete-event simulation model of the Niger vaccine supply chain, we simulated the impact of making different combinations of the six current EPI vaccines thermostable. FindingsMaking any EPI vaccine thermostable relieved existing supply chain bottlenecks (especially at the lowest levels), increased vaccine availability of all EPI vaccines, and decreased cold storage and transport capacity utilization. By far, the most substantial impact came from making the pentavalent vaccine thermostable, increasing its own vaccine availability from 87% to 97% and the vaccine availabilities of all other remaining non-thermostable EPI vaccines to over 93%. By contrast, making each of the other vaccines thermostable had considerably less effect on the remaining vaccines, failing to increase the vaccine availabilities of other vaccines to more than 89%. Making tetanus toxoid vaccine along with the pentavalent thermostable further increased the vaccine availability of all EPI vaccines by at least 1–2%. ConclusionOur study shows the potential benefits of making any of Niger's EPI vaccines thermostable and therefore supports further development of thermostable vaccines. Eliminating the need for refrigerators and freezers should not necessarily be the only benefit and goal of vaccine thermostability. Rather, making even a single vaccine (or some subset of the vaccines) thermostable could free up significant cold storage space for other vaccines, and thereby help alleviate supply chain bottlenecks that occur throughout the world.

Adaptive configuration of elastic high speed multiclass networks

Network design is a compromise between two conflicting requirements: high network efficiency and high quality of service (QoS). High efficiency suggests full sharing of network resources. However, in a multiclass network, QoS differentiation among several traffic classes suggests traffic segregation and resource partitioning. High efficiency in a partitioned network can be realized by elastic time-varying partitioning of the network capacity. The network can be laterally divided into bands, and each band may be reconfigured frequently, under the constraint of the fixed total capacity. Rapid partitioning is facilitated by two main developments: the capability of high-speed transfer of control data, and the ease of dynamic partitioning of link capacity. This article describes how elastic network bands are used to realize an efficient network serving heterogeneous traffic. It also discusses the intraband management of independent connections and reserved end-to-end paths so that the connection-request processing load is reduced while a high transport-capacity utilization is maintained.