Cold Chain Logistics Distribution Research Articles

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.

Literature Review on Fresh Products Cold Chain Logistics and Distribution Issues

In this paper, the literature on the concepts of fresh product cold chain logistics, the container operation problems related to cold chain transport, product order picking, distribution and the integration of the two problems are sorted out to provide theoretical references for the further study of the transport and distribution problems of fresh product cold chain logistics. Through combing the literature at home and abroad, the current fresh product cold chain logistics transport and distribution mainly exists in the container intermodal transport research object is single, mostly focusing on the railway container centre station; order distribution problems related research is less, vehicle path problem solving algorithms and related mathematical models are less; order picking and distribution of the joint research is less, and most of them stay in the theoretical stage, the method of landing is more difficult and other problems.

Review on Location of Fresh Cold Chain Logistics Distribution Center

This paper reviews the research status, existing problems and challenges, and future research directions of the location of fresh cold chain logistics distribution centers. The research background is based on factors such as the development of the fresh product market, the technological progress of cold chain logistics, the requirements of environmental protection and sustainable development, and the intensification of market competition. The significance of site selection includes improving transportation efficiency, reducing costs, improving customer satisfaction, optimizing supply chain networks, and achieving environmental sustainability.The former focuses on low-carbon, demand uncertainty, and competitive distribution center location, while the latter focuses on the new retail environment and cold chain distribution. The review of relevant literature points out that some progress has been made in the research, but there are challenges such as market demand uncertainty, incomplete data and limited model applicability.Future research directions include the location model of cold chain logistics distribution center based on big data, the location model considering sustainable development factors, and the location method of cold chain logistics distribution center integrating multi-index evaluation.In the conclusion, it is pointed out that in the past, the time window and the overall logistics network were rarely used as research evaluation indicators in the site selection problems, and the cost of reverse logistics and closed-loop supply chain was rarely considered. In the prospect part, it is proposed that in the future, we should pay attention to the problems of reverse logistics and closed-loop supply chain in the distribution of fresh agricultural products, consider the multi-objective optimization of low-carbon cold chain logistics network in different policies and fields, and combine full simulation technology and optimization technology to realize the system optimization research.

Cold Chain Logistics and Joint Distribution: A Review of Fresh Logistics Modes

With the continuous development of the global logistics industry, cold chain transportation and joint distribution, as critical strategies in supply chain management, are gradually becoming key means to ensure the safe transportation of perishable goods, pharmaceuticals, and other temperature-sensitive commodities. The present study is dedicated to an in-depth exploration of cold chain logistics and joint distribution, with a particular focus on a review of fresh food logistics modes, aiming to comprehensively understand their operational modes, advantages, challenges, and future development trends. The present study elucidates the basic concepts of fresh food logistics and underscores its significance in supply chain management. Through comparative analysis of different operational modes, it reveals their advantages in enhancing efficiency, reducing costs, and mitigating environmental impacts. The present study focuses on the operational mode of joint distribution, discussing its application in cold chain logistics and its differences from traditional logistics modes. Through case studies and empirical analysis, it evaluates the impact of joint distribution on logistics efficiency and costs, as well as its potential to enhance transportation efficiency and reduce carbon emissions. Lastly, the present study provides an outlook on the future development trends of cold chain logistics and joint distribution, discussing the influences of technological innovation, policy support, and industry collaboration and offering recommendations and prospects to drive the sustained development of the industry. Through a comprehensive summary of fresh food logistics, cold chain logistics operational modes, and joint distribution operational modes, this paper aims to provide in-depth theoretical support and practical guidance for related research and practices.

Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center

AbstractIn recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarantee the fresh food products for the time and quality. In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed.

Application of EIQ-ABC Analysis Method in Warehouse Management of X Cold Chain Logistics Distribution Center

Application of EIQ-ABC Analysis Method in Warehouse Management of X Cold Chain Logistics Distribution Center

Application of Improved Genetic Algorithm and Deep Learning in Cold Chain Logistics Distribution Demand Prediction

In order to solve the problem of inaccurate prediction results caused by the excessive impact of downstream on upstream suppliers in the process of cold chain logistics transportation demand prediction, the author proposes a demand prediction system Multi agent based on improved genetic algorithm and deep learning. The system will improve genetic algorithm, combine deep learning with practical problems in cold chain logistics supply chain, and evaluate the improved model through instance simulation. The results are as follows: After optimization, the order quantity of each stratum reduces the influence of retailers on upstream suppliers by more than 70%. As for the overall transportation cost, it shows a continuous upward trend within 20 cycles, while the total cost of each cycle fluctuates in a lower range after optimization, reducing the overall total cost by about 50%. It shows the reliability of the improved demand forecasting system in this study to greatly reduce storage and transportation costs.

Fresh agricultural products cold chain logistics distribution and path optimization

Based on the reference to the existing research results, combined with the enterprise's current distribution path, to minimize the cost as the research objective, to establish the relevant model, and put forward the control of logistics costs, increase the infrastructure investment in cold chain logistics, the optimization of the path of countermeasure proposals, to further improve the efficiency of the enterprise distribution and increase customer satisfaction at the same time reduces the cost of distribution, increase the core competitiveness of the industry.

A cold chain logistics distribution optimization model: Beijing-Tianjin-Hebei region low-carbon site selection

PurposeThis study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.Design/methodology/approachThis study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.FindingsThe optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.Originality/valueThis study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

Retraction Note to: A Hierarchical Algorithm Model for the Scheduling Problem of Cold Chain Logistics Distribution Vehicles Based on Machine Vision

Retraction Note to: A Hierarchical Algorithm Model for the Scheduling Problem of Cold Chain Logistics Distribution Vehicles Based on Machine Vision

A multi-objective optimization model for the location of cold chain logistics distribution center based on trust domain optimization algorithm

Cold chain transportation refers to a logistics method that transports fresh, perishable, and perishable items from the place of production, processing or warehouse to the place of consumption under certain temperature conditions. As consumers have higher and higher requirements for food safety and quality, the cold chain logistics industry has also developed rapidly. However, the high cost of cold chain logistics, the difficulty of technology, the difficulty of ensuring service quality and other problems have also arisen, and how to optimize cold chain transportation has become a hot issue in the cold chain logistics industry. Cold chain transportation optimization refers to the premise of ensuring the quality and safety of goods, through reasonable transportation paths, transportation methods, temperature control and other measures, to minimize the cost of cold chain transportation, improve efficiency and service quality. In order to achieve the optimization of cold chain transportation, it is necessary to establish a reliable cold chain logistics distribution center to ensure the safety and quality of goods during transportation. In order to solve the problem of location selection of cold chain logistics distribution center, this paper first defines the service reliability and calculation method of cold chain distribution center. Then, the location model of the cold chain logistics distribution center and the trust domain optimization algorithm model were established. The model aims to minimize the total cost, while considering multiple factors such as transportation distance, temperature control, facility construction, etc., to ensure the reliability and operational efficiency of the cold chain logistics distribution center. Finally, this paper introduces an example for calculation to prove the feasibility and universality of the model in the location problem of cold chain logistics distribution center. Through the calculation of examples, it can be seen that the model can effectively reduce the cost of cold chain transportation and improve the service quality and efficiency of cold chain logistics distribution center. In summary, this paper proposes a reliable location model and trust domain optimization algorithm model for cold chain logistics distribution centers to solve the challenges faced by the cold chain logistics industry. This model can provide guidance for cold chain logistics companies to gain a greater advantage in a highly competitive market.

Research on Optimization of Agricultural Products Cold Chain Logistics Distribution System Based on Low Carbon Perspective

Based on thindiscussion of the traditional agricultural product distribution model, this article establishes a low-carbon perspective of urban agricultural product co-distribution model to reduce the level of agricultural product circulation and reduce the impact of distribution activities on the environment. By comprehensively considering the factors affecting carbon emissions in the vehicle delivery process, the fuel consumption and carbon emissions estimation models of delivery vehicles are analyzed and put forward. A mathematical model for the optimization of urban agricultural product cold chain distribution routes from a low-carbon perspective is established. This article takes a logistics center as an example, selects genetic algorithm as the model solution method, optimizes the distribution route, and obtains the corresponding result, thus verifying the rationality and feasibility of the model.

Hybrid Tabu-Grey wolf optimizer algorithm for enhancing fresh cold-chain logistics distribution.

The increasing public demand for fresh products has catalyzed the requirement for cold chain logistics distribution systems. However, challenges such as temperature control and delivery delays have led a significant product loss and increased costs. To improve the current situation, a novel approach to optimize cold chain logistics distribution for fresh products will be presented in the paper, utilizing a hybrid Tabu-Grey wolf optimizer (TGWO) algorithm. The proposed hybrid approach combines Tabu search (TS) and Grey wolf optimizer (GWO), employing TS for exploration and GWO for exploitation, aiming to minimize distribution costs in total and establish efficient vehicle scheduling schemes considering various constraints. The effectiveness of the TGWO algorithm is demonstrated through experiments and case studies compared to other heuristic algorithms. Comparative analysis against traditional optimization methods, including Particle swarm optimization (PSO), Whale optimization algorithm (WOA), and original GWO, highlights its superior efficiency and solution quality. This study contributes theories by demonstrating the efficacy of hybrid optimization techniques in complex supply chain networks and dynamic market environments. The practical implication lies in the implementation of TGWO to bolster distribution efficiency, cost reduction, and product quality maintenance throughout the logistics process, offering valuable insights for operational and strategic improvements by decision-makers. However, the study has limitations in generalizability and assumptions, suggesting future research areas including exploring new search operators, applying additional parameters, and using the algorithm in diverse real-life scenarios to improve its effectiveness and applicability.

Simulation Research on Logistics Distribution Path Based on Colony Intelligence Optimisation

Abstract In light of the growing emphasis on “logistics integration,” this paper contends that the logistics network system requires comprehensive integration and optimization. We propose the use of the Bacterial Foraging Optimization (BFO) algorithm to enhance the Vehicle Routing Problem (VRP). The penalty function method is employed to direct the BFO algorithm in identifying the optimal vehicle path encoding and to improve the convergence operations for logistics distribution. This study analyzes the fundamental characteristic elements of the VRP, introduces a basic model for the VRP, and develops a logistics distribution path optimization model that minimizes the total cost by thoroughly considering the expenses associated with cold chain low-carbon logistics distribution. A simulation environment is established, and algorithm parameters are set to determine the optimal solutions for both the BFO and the Improved BFO (IBFO) algorithms in the test function. An example is selected for practical application, wherein the design of the distribution center and points is carried out, and the colony intelligence optimization algorithm is applied to simulate the logistics and distribution paths. Combined with the specific case of cold chain distribution of food, the optimization of the cold chain logistics distribution path is solved. In the case study, when the carbon penalty coefficient is ε = 15, the optimal logistics and distribution site selection program is Guangxi and Guizhou, and the total cost of the supply chain is 16,363,365.92 yuan. At this time, the supply chain cost is optimal. Compared with the carbon penalty coefficient ε = 20, the economic cost increased by 70152.24 yuan, but the carbon emission decreased by 1890.9 kg. The optimization of logistics and distribution processes encourages enterprises to develop strategies that promote low carbon and environmental protection and achieve better economic and ecological outcomes.

Optimization of low‐carbon cold chain logistics distribution path for agricultural products based on two‐stage algorithm

AbstractWith the development of market economy, cold chain logistics has become the mainstream of the current transportation industry. Reducing transportation costs and optimizing transportation routes from an environmentally friendly perspective is the main research focus. This study starts with an emphasis on environmental protection and cost savings and optimizes existing cold chain logistics expenses. Using the clustering and annealing algorithms, the path optimization model with the lowest cost is constructed and analyzed. The K‐means algorithm is utilized to cluster and partition logistics areas, and then optimized simulated annealing algorithm is used to control and utilize logistics costs and resources. The experimental results show that the optimized algorithm reduces costs by 11.36% and increases the loading rate of the vehicle by 11.95%. The delivery time has been reduced by 18.1%. The two‐stage algorithm can optimize and improve the path model, reduce transportation costs, improve cold chain transportation efficiency, and verify the feasibility of the model.

Environmental cold chain distribution center location model in the semiconductor supply chain: A hybrid arithmetic whale optimization algorithm

This study addresses the high cost and high carbon emissions associated with the transportation sector. An environmental cold chain logistics distribution center location model has been designed by considering various constraints such as demand, time windows, and cost factors associated with cargo damage, refrigeration of cold chain cargo, and carbon emissions. An environmental cold chain logistics distribution center location model is designed for the raw materials of low-temperature storage and transportation in the semiconductor supply chain to achieve sustainable development by reducing carbon emissions. This study effectively reduces transportation costs and carbon emissions. To address the issues of slow convergence speed and susceptibility to local optima in the conventional whale optimization algorithm (WOA), a hybrid arithmetic whale optimization algorithm (HAWOA) is proposed by combining arithmetic optimization and the honey badger algorithm. Simulation analysis shows that the HAWOA is capable of obtaining the location scheme with the minimum distribution cost under the same number of iterations, which provides a substantial advantage compared to other algorithms.

An Enhanced Ant Colony Algorithm-Based Low-Carbon Distribution Control Method for Logistics Leveraging Internet of Things (IoT)

This paper presents a low-carbon vehicle routing optimization model to reduce energy consumption and carbon emissions in logistics and distribution. The model is solved using a hybrid algorithm of simulated annealing and ant colony optimization. It enhances the information pheromone concentration update process and directionality by introducing a carbon emission factor and a multifactor operator. Additionally, an adaptive elite individual reproduction strategy is employed to improve algorithm efficiency. In this case study focusing on cold chain logistics distribution, both the model and algorithm under consideration were evaluated. The findings affirm the effectiveness of the model in reducing carbon emissions and demonstrate the efficiency and robustness of the algorithm. Through this analysis, the paper sheds light on environmentally sustainable practices in logistics distribution.

RETRACTED ARTICLE: A Hierarchical Algorithm Model for the Scheduling Problem of Cold Chain Logistics Distribution Vehicles Based on Machine Vision

With the continuous development of the market economy, the professional degree of the logistics industry is constantly improving, while the logistics distribution industry is also developing rapidly. The logistics distribution of the cold chain supply chain involves multiple distribution points, and the distance and time relationship between the distribution points are often not fully considered in the route planning, resulting in low distribution efficiency. The hierarchical algorithm model based on machine vision can solve the above problems to a certain extent. This paper takes two cold chain supply chain enterprises as the main research body, analyzes how to choose two kinds of COD and CCD sensors using machine vision, and the number of distribution vehicle scheduling. The simulation experiment was performed and at the end of the article it is summarized and discussed. According to the data sample, the two enterprises have the largest number of people satisfied with the supply chain logistics and distribution vehicle scheduling, but the number of people dissatisfied with enterprise A is 6 and 12% of the total. The number of people dissatisfied with enterprise B is 16 and 32% of the total number, It can be seen that although the number of people satisfied with the two enterprises is large, the number of people dissatisfied with enterprise B far exceeds that of enterprise A. At the same time, with the continuous research of supply chain logistics distribution vehicle scheduling, the research on machine vision is also facing new opportunities and challenges.

Optimization of perishable agricultural products logistics distribution path based on IACO-time window constraint

With the development of modern logistics industry, the cold chain logistics distribution of perishable agricultural products has become an important link to ensure food quality and safety. Aiming at the complicated situation in the process of perishable agricultural products transportation path planning, a cold chain logistics distribution path optimization model based on Ant Colony Optimization (ACO) was proposed. Based on the traditional soft and hard time window constraint model, an optimized time window constraint model was proposed, and the update function of pheromone increment was substituted to optimize the traditional ant colony algorithm. An Improved Ant Colony Optimization (IACO)-time-window constrained path optimization model was proposed. The test results showed that in the convergence training experiment in Matlab environment, the research method only needed 19 iterations to reach the lowest level. In the experiment of application effect, the length of the path generated by the research method for car a was 188.93 km. Car Group a could complete 60.38 % offload at the fourth distribution node. The experimental results showed that the proposed route optimization model had better iteration efficiency and could effectively generate a shorter distance distribution path, which provides a new technical support for the route optimization of cold chain distribution of perishable agricultural products.

RESEARCH ON THE OPTIMIZATION OF FRESH AGRICULTURAL PRODUCT COLD CHAIN LOGISTICS DELIVERY PATH

Due to the improvement of the economic level, people's living quality is getting higher and higher. Fresh agricultural products are part of our lives and closely related to each other. However, the cold chain logistics system in China is not yet mature. Fresh agricultural products deteriorate, causing severe waste. In order to improve this phenomenon, the cold chain logistics distribution path of fresh agricultural products should be optimized, the efficiency of cold chain logistics should be improved, and the delivery cost of fresh agricultural products should be reduced to meet people's demand for fresh agricultural products. This article analyzes the problems in the cold chain logistics distribution of fresh agricultural products and explores the optimization strategy of the supply chain logistics path of fresh agricultural products.