Cold Chain Logistics Research Articles

Cold chain logistics performance: a framework

Cold chain logistics performance: a framework

Research on Innovative Management of Smart Cold Chain Logistics: Taking Cobia Shanwei of Guangdong as an Example

Research on Innovative Management of Smart Cold Chain Logistics: Taking Cobia Shanwei of Guangdong as an Example

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.

Regional efficiency analysis of fresh food cold chain logistics in China based on three-stage DEA model

PurposeAssessing the efficiency of fresh food cold chain logistics as accurately as possible is essential for industry development planning. This study was designed to analyze the efficiency of fresh food cold chain logistics in China.Design/methodology/approachA three-stage data envelopment analysis (DEA) model was used to analyze the efficiency of fresh food cold chain logistics in 30 provinces of China from 2013 to 2019. The stochastic frontier analysis (SFA) model in the second stage was used to eliminate the influence of external environmental factors and random disturbances on efficiency analysis results.Findings(1) The overall actual efficiency of fresh food cold chain logistics in China is unsatisfactory, with an average technical efficiency of 0.382 over the 7-year period. (2) The national average technical efficiency and average scale efficiency were overestimated by 29.9% and 40.0%, respectively, compared with the actual values. (3) The efficiency of fresh food cold chain logistics does not align with the level of regional economic development. (4) Distinct regional variations exist in the efficiency of fresh food cold chain logistics in China, with higher efficiencies observed in Northwest China and the Central Yangtze River regions, and the lowest efficiencies in the northeast regions.Originality/valueThis study applies a three-stage DEA model to assess the development and regional differences of fresh food cold chain logistics in China, enriching the application of models and empirical analysis in this field. By analyzing the situation in China, it provides ideas and references for other developing countries to develop cold chain logistics.

Cross-Docking Layout Optimization in FlexSim Software Based on Cold Chain 4PL Company

The paper highlights the potential of cross-docking to reduce storage time and costs. The study addresses evolving market demands that push logistics providers to adopt new technologies for operational efficiency, emphasizing the often-overlooked importance of optimizing cross-docking layouts. The research, conducted in two phases, first analyzed the current warehouse layout (Variant I) to identify inefficiencies and then designed a new layout (Variant II) that was simulated using FlexSim 2022 software. The results showed significant improvements with the new layout, including a 35% increase in deliveries and a 3.23% reduction in forklift travel distances, leading to lower operational costs. Even minor adjustments in the warehouse design proved to enhance logistics efficiency, particularly during peak demand periods like holidays. The study demonstrates how FlexSim software can be applied in cold chain logistics to optimize warehouse operations, underscoring the benefits of cross-docking for cost-effective logistics management.

Stable and sprayed cesium-lead-halide perovskite triggered visual temperature sensor for cold chain transport

Temperature sensing is significant in cold chain logistics, but developing a cost-effective temperature indicator that can be produced on a large scale remains a considerable challenge. In this study, a highly efficient, cost-effective, and amenable to large-scale production perovskite fluorescent temperature sensor was developed based on the strong linear photoluminescence dependence of cesium lead bromide perovskite nanocrystals (CsPbBr3 NCs), utilizing the dual confinement of liquid nitrogen and N,N-dimethylformamide (DMF). Due to the introduction of liquid nitrogen, CsPbBr3 NCs were able to stabilize, and the precursor solution can remain unchanged for over 30 days under low-temperature conditions. This fluorescent temperature sensor would gradually change its blue light from 440 nm to a bright green (524 nm) as the temperature rises to room temperature (25 °C). More importantly, due to nano nano-fibered CsPbBr3 NCs temperature sensor prepared via electrospinning process can directly contact with the atmosphere, it would facilitate rapid recrystallization and results in a swift color change from blue to green within 24 h. These characteristics demonstrate significant potential for applications in temperature sensing, especially for cold chain logistics to monitor the transportation of agricultural products, processed foods, and special items.

An assessment of service quality for cold-chain logistics in air freight: A Perception-Expectation gap model based on fuzzy Best-Worst Method

Recently, the requirements for cold-chain logistics in air freight (CLAF) have appeared to grow steadily. However, such an issue has been discussed less in the relevant research. The main purpose of this research is to evaluate the CLAF's service quality. In this paper, a Perception-Expectation gap model based on the fuzzy Best-Worst Method (BWM) is proposed to evaluate the service quality of CLAF. A typical CLAF operator with its main shippers in Taiwan was then empirically investigated to validate the proposed model. The result shows that shippers are mostly concerned with the service qualities of Stable and multiple shipping spaces, Pricing reasonableness, and Perfect cargo delivery. Based on the results, theoretical and managerial implications are discussed. The results can provide practical information for air freight operators to make managerial policies to improve their cold-chain operational performances. Further, the proposed model can provide a theoretical reference regarding the service quality gap in practical applications.

Impact of magnetic field-assisted freezing on the physicochemical properties and starch structure of cooked rice: Effects of magnetic types, intensities, and cryostasis time

A magnetic field-assisted freezing system was developed to mitigate the degradation of taste quality in frozen cooked rice (FCR). The physicochemical properties and starch structure were analyzed under varying magnetic field types, intensities, and cryostasis time. The analysis of freezing characteristics indicated that treatments with 10 mT static magnetic fields (SMF) and 6 mT alternating magnetic fields (AMF) yielded optimal results, significantly reducing the duration of the maximum ice crystal generation zone by approximately 18 min. Compared to no magnetic field (NMF) treatment, a 16-day frozen storage experiment showed significant improvements in the texture characteristics of cooked rice treated with magnetic fields. However, the moisture content of rice treated with AMF closely resembled those of freshly cooked rice, with a slight increase in yellowness compared to SMF treatment. Throughout the storage period, the crystallinity for the AMF treatment exceeded that of the SMF treatment by 2.99 %. Furthermore, compared to SMF treatment, water molecules in FCR treated with AMF are more tightly bound. Given the superior sensory scores in the AMF treatment, it can be concluded that while SMF reduces color degradation, AMF is more effective in preserving moisture, and structural density. Hence, magnetic fields, especially AMF, emerge as a promising auxiliary technology for FCR, offering a theoretical basis for advancing cold chain logistics technology for cooked rice.

Research on High-quality Development of Premade Food Industry from the Perspective of Supply Chain Management -- Take Freshippo as an Example

In recent years, with the acceleration of people's pace of life, the concept of premade food continues to be hot, the premade food industry has developed rapidly as well as the market scale has expanded. Supply chain is a crucial link in premade food industry chain. The proper supply chain management is of great significance to the high-quality development of the precooked dish industry. At present, there are still a series of challenges and deficiencies in the supply chain management of the prepared dish industry. Perfect food safety supervision system, sinking cold chain logistics network and intelligent supply chain management have become the focus of sustainable development of this field. This paper selects Freshippo as the research object, studying the challenges and development opportunities faced by the current premade food industry in the supply chain management through the case analysis method, and then proposes corresponding supply chain management optimization countermeasures to solve these problems, aiming to help the healthy and vigorous development of the premade food industry.

Research on the Application of Blockchain Technology in Cold Chain Logistics for Agricultural Products

With the continuous advancement of science and technology and the advent of the digital era, blockchain technology is increasingly demonstrating its great potential across various industries due to its unique features of decentralization, transparency, and immutability. In particular, in the cold chain logistics of agricultural products, the application of blockchain technology can not only enhance logistics efficiency but also ensure food safety and boost consumer trust. This paper first outlines the advantages of blockchain technology in cold chain logistics for agricultural products, and then clarifies the application pathways of blockchain technology in this field, providing a reference for relevant researchers.

Understanding Viral Haemorrhagic Fevers: Virus Diversity, Vector Ecology, and Public Health Strategies.

Viral haemorrhagic fevers encompass a diverse group of severe, often life-threatening illnesses caused by viruses from multiple families, including Arenaviridae, Filoviridae, Flaviviridae, Hantaviridae, Nairoviridae, Peribunyaviridae, and Phenuiviridae. Characterised by fever and haemorrhagic symptoms, these diseases challenge public health systems by overwhelming healthcare facilities, complicating diagnostic processes, and requiring extensive resources for containment and treatment, especially in resource-limited settings. This discussion explores the intricate relationships between VHFs and their transmission vectors-both animal and arthropod-and examines the impact of ecological and geographic factors on disease spread. The primary transmission of VHFs typically occurs through direct contact with infected animals or via bites from haematophagous arthropods, facilitating zoonotic and, at times, human-to-human transmission. With an emphasis on the role of diverse wildlife, domesticated animals, and vectors such as mosquitoes and ticks in the epidemiology of VHFs, there is a recognised need for robust surveillance and strategic public health responses to manage outbreaks. This review discusses the necessity of interdisciplinary approaches that integrate virology, ecology, and public health to enhance diagnostic capabilities, develop vaccines and antivirals, and improve outbreak interventions. Exploring the ecological and biological dynamics of VHFs will help bolster a deeper understanding of these emerging viruses and underpin preparation for future outbreaks. The importance of enhanced global cooperation, continuous research, and collaboration to mitigate the public health threats posed by these complex infections is a central theme, serving as a foundational strategy to reinforce worldwide preparedness and response efforts. Future directions include addressing gaps in vaccine development and tailoring public health strategies to the unique challenges of managing VHFs, such as the rapid mutation rates of viruses, the need for cold chain logistics for vaccine distribution, and socio-economic barriers to healthcare access, in order to ensure readiness for and effective response to emerging threats worldwide.

Construction of a blockchain based cold chain logistics information platform for Gannan navel oranges to enhance transparency and efficiency

As a high-value agricultural product, the cold chain logistics management of Gannan navel oranges has global significance. Especially in Africa and Europe, food safety and supply chain quality are critical issues. However, the existing Gannan navel orange logistics information management system relies on traditional databases and information systems, with insufficient data sharing and transparency, affecting the overall coordination of the supply chain and customer satisfaction. In addition, the traditional system is vulnerable to hacker attacks and malicious tampering of data by insiders, resulting in serious economic losses and reputation damage. So the blockchain platform constructed in this study improves the transparency and traceability of logistics data through the SMART-PBFT algorithm of the alliance chain, which optimizes the logistics management process, improves the quality of logistics services, and reduces operating costs. It improves the logistics efficiency and data transparency of local agricultural products, and also provides a demonstrative case for the cold chain management of other high-value agricultural products around the world, with broad application potential and reference value.

Stage-Specific Multi-Objective Five-Element Cycle Optimization Algorithm in Green Vehicle-Routing Problem with Symmetric Distance Matrix: Balancing Carbon Emissions and Customer Satisfaction

This study presents a bi-objective optimization model for the Green Vehicle-Routing Problem in cold chain logistics, with a focus on symmetric distance matrices, aiming to minimize total costs, including carbon emissions, while maximizing customer satisfaction. To address this complex challenge, we developed a Stage-Specific Multi-Objective Five-Element Cycle Optimization algorithm (MOFECO-SS), which dynamically adjusts optimization strategies across different stages of the process, thereby enhancing overall efficiency. Extensive comparative analyses with existing algorithms demonstrate that MOFECO-SS consistently outperforms in solving the multi-objective optimization model, particularly in reducing total costs and carbon emissions while maintaining high levels of customer satisfaction. The symmetric nature of the distance matrix further aids in achieving balanced and optimized route planning. The results highlight that MOFECO-SS offers decision-makers flexible route planning options that balance cost efficiency with environmental sustainability, ultimately improving the effectiveness of cold chain logistics operations.

A Review of Advanced Sensor Technologies for Aquatic Products Freshness Assessment in Cold Chain Logistics.

The evaluation of the upkeep and freshness of aquatic products within the cold chain is crucial due to their perishable nature, which can significantly impact both quality and safety. Conventional methods for assessing freshness in the cold chain have inherent limitations regarding specificity and accuracy, often requiring substantial time and effort. Recently, advanced sensor technologies have been developed for freshness assessment, enabling real-time and non-invasive monitoring via the detection of volatile organic compounds, biochemical markers, and physical properties. The integration of sensor technologies into cold chain logistics enhances the ability to maintain the quality and safety of aquatic products. This review examines the advancements made in multifunctional sensor devices for the freshness assessment of aquatic products in cold chain logistics, as well as the application of pattern recognition algorithms for identification and classification. It begins by outlining the categories of freshness criteria, followed by an exploration of the development of four key sensor devices: electronic noses, electronic tongues, biosensors, and flexible sensors. Furthermore, the review discusses the implementation of advanced pattern recognition algorithms in sensor devices for freshness detection and evaluation. It highlights the current status and future potential of sensor technologies for aquatic products within the cold chain, while also addressing the significant challenges that remain to be overcome.

Effects of Cold Chain Logistics of Fresh Foods Service Quality on Users: The Adjustment Effect of Usage Frequency

Effects of Cold Chain Logistics of Fresh Foods Service Quality on Users: The Adjustment Effect of Usage Frequency

Design of innovative phase-change cold storage refrigerator and simulation analysis of discharging progress

At present, the field of cold chain logistics experiences significant growth, with refrigerator playing a pivotal role in cold chain transportation. An innovative compartmentalized phase-change cold storage refrigerator has been proposed in this study, designed to address the increasing demand for efficient and energy-saving solutions in the cold chain transportation industry. A conceptual module prototype is designed and built in this study, with an analysis of the system's charging and discharging processes under varying conditions. The cold storage refrigerator exhibits favorable matching characteristics, the charging process requires approximately 270 min, and the cooling effect sustains for about 23 h. A three-dimensional simulation model of the cold storage refrigerator is developed, enabling a comprehensive evaluation of the cooling effect and further optimization of the cold storage plate layout. The results indicate that the layout of the three-sided type cold plate significantly reduces the pre-cooling time. It is determined through simulation calculations in this study that setting the loading capacity to 50 % can strike a balance between efficient cooling and transportation efficiency. Additionally, under high-temperature conditions, the cold storage refrigerator maintains a low temperature for up to 10 h at a filling rate of 50 %.

Optimization of frozen goods distribution logistics network based on k-means algorithm and priority classification.

Maintaining the quality and integrity of frozen goods throughout the supply chain necessitates a robust and efficient cold chain logistics network. This research proposes a machine learning-based method for optimizing such networks, resulting in significant cost reduction and resource utilization improvement. The method employs a three-phase approach. First, K-means clustering groups sellers based on their geographical proximity, simplifying the problem and enabling more accurate demand prediction. During the second phase of the proposed method, Gaussian Process Regression models predict future sales volume for each seller cluster, leveraging historical sales data. Finally, the Capuchin Search Algorithm simultaneously optimizes distributor location and resource allocation for each cluster, minimizing both transportation and holding costs. This multi-objective approach achieved a 34.76% reduction in costs and a 15.6% reduction in resource wastage compared to the existing system. This novel method offers a valuable tool for frozen goods distribution networks, with advantages such as considering multiple goals for optimization, focusing on demand prediction, potential for reduced complexity, and focusing on managerial insights over compared methods.

A Review of the Energy-Saving Potential of Phase Change Material-Based Cascaded Refrigeration Systems in Chinese Food Cold Chain Industry

As the global demand for food increases, the efficiency and environmental sustainability of refrigeration systems have become increasingly critical issues. Cascaded refrigeration systems (CRSs) are widely used in the Chinese food cold chain due to their capacity to meet a wide range of temperature requirements. However, energy consumption of these systems is always high. If phase change materials (PCMs) are combined with the refrigeration systems, the energy-saving effect is remarkable. The paper reviews the integration of PCMs within CRS, focusing on their potential to reduce energy consumption, thereby improving food safety and reducing reliance on conventional, electricity-intensive refrigeration methods. The study categorizes and explores the low-temperature applications of PCMs in CRS, providing novel insights into enhancing energy efficiency in food cold chain logistics. Despite most PCM research focusing on single-stage systems, this review innovates by introducing PCM integration in multistage cascade systems, which is particularly relevant for low-temperature requirements. The discussion encompasses the structure, working fluids, and applications of CRSs in the cold chain, emphasizing the role of PCMs in sustainable cold chain management. The review concludes by highlighting the need for further research on PCMs in CRS, especially regarding their economic viability and large-scale implementation potential.

Optimization of distribution paths in cold chain logistics management based on IFW-ABC algorithm

The current cold chain logistics management and distribution routes generally face problems such as environmental pollution and high costs. Therefore, the study proposed an improved fireworks-artificial bee colony for optimizing delivery paths. Firstly, the artificial bee colony was improved by using neighborhood search. Secondly, for the optimal solution, the fireworks explosion operator was used for the final result search. The benchmark function validation showed that the proposed algorithm performed better than other algorithms in solving optimal value, average value, and standard deviation. In the simulation analysis of a fresh enterprise in China, the total delivery cost was reduced by an average of 3.30% and 4.93% compared to other algorithms, considering carbon emission and not considering it, respectively. This proposed algorithm had more advantages in reducing quality loss, pollutant emissions, and CE. Therefore, this improved fireworks-artificial bee colony can effectively reduce the economic costs and environmental pollution of cold chain logistics distribution routes. This ensures economic benefits while considering social benefits, achieving the optimal path planning for logistics distribution.

Vehicle routing Problem for cold chain logistics based on data fusion technology to predict travel time

Vehicle routing Problem for cold chain logistics based on data fusion technology to predict travel time