A Benchmark of Video-Based Clothes-Changing Person Re-Identification

Person re-identification (Re-ID) is a classical computer vision task and has achieved great progress so far. Recently, long-term Re-ID with clothes-changing has attracted increasing attention. However, existing methods mainly focus on image-based setting, where richer temporal information is overlooked. In this paper, we focus on the relatively new yet practical problem of clothes-changing video-based person re-identification (CCVReID), which is less studied. We systematically study this problem by simultaneously considering the challenge of the clothes inconsistency issue and the temporal information contained in the video sequence for the person Re-ID problem. Based on this, we develop a two-branch confidence-aware re-ranking framework for handling the CCVReID problem. The proposed framework integrates two branches that consider both the classical appearance features and cloth-free gait features through a confidence-guided re-ranking strategy. This method provides the baseline method for further studies. Also, we build two new benchmark datasets for CCVReID problem, including a large-scale synthetic video dataset and a real-world one, both containing human sequences with various clothing changes. We will release the benchmark and code in this work to the public

An Optimization Approach to the Intermodal Transportation Network in Fruit Cold Chain, Considering Cost, Quality Degradation and Carbon Dioxide Footprint

This model optimizes port hinterland intermodal refrigerated container flows, considering both cost and quality degradation, which is distinctive from the previous literature content in a way that it quantifies the influence of carbon dioxide (CO2) emission in different setting temperature on intermodal network planning. The primary contribution of this paper is that the model is beneficial not only to shippers and customers for the novel service design, but also offer, for policy-makers of the government, insights to develop inland transport infrastructures in consideration of intermodal transportation. The majority of models of multimodal system have been established with an objective of cost minimization for normal commodities. As the food quality is possible to be influenced by varying duration time required for the storage and transportation, and transportation accompanied with refrigeration producing more CO2 emission, this paper aims to address cost minimization and quality degradation minimization within the constraint of CO2 footprint. To achieve this aim, we put the quality degradation model in a mixed-integer linear programming model used for intermodal network planning for cold chain. The example of Dalian Port and Yingkou Port offer insight into trade-offs between transportation temperature and transport mode considering CO2 footprint. Furthermore, the model can offer a useful reference for other regions with the demand for different imported food, which requires an uninterrupted cold chain during the transportation and storage

Simulation-Based Optimization for Yard Design at Mega Container Terminal under Uncertainty

The conventional approach of designing a container yard should be reexamined in the context of sustainable port development. Considering the uncertain future throughput, a simulation-based optimization framework is proposed to obtain a cost-effective and reliable design solution to the physical layout and equipment deployment strategy of the yard at a mega container terminal. In this framework, a two-stage stochastic programming model is presented aided with a simulation procedure of terminal operations. Finally, an application is given and the results show that the proposed integrated decision framework is effective and helpful for optimizing container yard design in the context of sustainable development of container terminals

Performance Comparison of Real-Time Yard Crane Dispatching Strategies at Nontransshipment Container Terminals

Yard crane operations are often a bottleneck at a container terminal. This paper aims to investigate the effects of various real-time yard crane dispatching strategies on operational cost and gross crane rate (GCR) for nontransshipment container terminals. A general cost estimation model is introduced to incorporate the detailed costs incurred during container handling process within terminal area. The formulas of container handling related parameters are mathematically derived to validate the simulation model. Results reveal that the common nearest truck first served strategy yields the lowest operational cost but the lowest GCR. On the other hand, earliest YT strategy achieves the highest GCR at the expense of higher operational cost with more vessel calls, while nearest YT strategy produces the highest GCR and is the second economical with fewer vessel calls. Under any of the proposed yard crane dispatching strategies, the strategy that separately stacks import and export containers into different blocks outperforms the scattered stacking strategy in terms of GCR, although no distinct cost advantage is obtained. The results provide fundamental insights into the connection between real-time yard crane dispatching strategies and operational performance at manually controlled nontransshipment container terminals

A Simulation-Based Dynamic Programming Method for Interchange Scheduling of Port Collecting and Distributing Network

As one of the effective methods to reduce congestion, grade intersection has already been changed to interchange in port collecting and distributing network (PCDN) of many Chinese ports, since the first interchange was built in the PCDN of Dalian port in 1924. Due to the growing demand for port freight transportation, congestion in PCDN is becoming one of the inevitable problems that need to be solved. This paper addresses the best interchange scheduling multistage decision problem in PCDN at a network level. The main challenges are how to estimate the delay time and cope with high uncertainties in port network and PCDN. Therefore, a simulation-based dynamic programming (DP) model is proposed with the purpose of minimizing total cost in lifetime period by combining a DP model and two nested simulation models together. Two simulation models are built to figure out the delay cost in the optimization model, which cannot be calculated by mathematical analysis due to complex vehicle travel patterns and irregular traffic volume caused by random events, such as the arrival pattern of ships’, natural conditions, and storage period of cargos. Finally, a real project in northern China is presented as a case study. The proposed method can be applied in similar cases and can help solve analogous complicated multistage problems

A Method for Determining the Required Power Capacity of an On-Shore Power System Considering Uncertainties of Arriving Ships

The contribution of this paper is to provide a method for determining the required power capacity of an on-shore power system (OPS) considering the stochastic nature of arriving ships. In order to cope with such complicated and stochastic operation processes in container terminals, simulation models are established with arrival intervals of ships ranging from 1 to 100 h as inputs. Firstly, the mobile pattern of OPS adopted in the container terminal is introduced. Then, patterns of arriving ships are analyzed to explain why a simulation method is necessary. Next, a series of simulation experiments based on a container terminal in China are constructed and carried out. Finally, the required power capacity of an OPS under different arrival intervals is given when considering all berthed ships using an OPS. Besides, with the consideration of reducing environmental impact of ships at different levels, the required power capacity is provided with different proportions of arriving ships using an OPS. The results obtained, and the proposed method can be used to provide references for government policy making and green container terminal construction