Logistics Network Optimization Research Articles

Optimization of reverse logistics network for end-of-life vehicles: A Shanghai case study

With the surge in car ownership, the end-of-life vehicles recycling market has shown enormous development potential. As the reverse logistics network for recycling end-of-life vehicles suffers from high operating costs and low recycling rates, there is an urgent need to upgrade the actual recycling measures for end-of-life vehicles to an operable level. This article first uses the OGM (1, N) model to predict the number of end-of-life vehicles in the coming years. At the same time, a reverse logistics network model with the second-hand car market as the recycling centre was constructed with the goal of minimizing the total cost of the end-of-life vehicles reverse logistics network. The network model was simulated using mixed integer programming (MILP), and the optimal solution was solved through LINGO 12 programming. Through an example analysis of Shanghai, it is found that the market of end-of-life vehicles will embrace growth, and it is verified that the optimized reverse logistics network can effectively reduce the operation cost and logistics cost of recycling centres, and can effectively improve the actual recycling rate of end-of-life vehicles. Finally, the optimized site selection results are obtained, and a specific traffic distribution scheme is proposed, which is crucial for promoting cars that meet scrap standards to be recycled through formal channels and reducing logistics costs for recycling enterprises.

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.

Optimisation of a multilevel logistics network for prepositioned warehouses under an omni-channel retail model

A new omni-channel retailing mode, prepositioned warehouses, which developed rapidly in China during the COVID-19 pandemic, was introduced, and a three-level logistics network optimisation model for agricultural products was presented. This study takes into account the characteristics of the omni-channel retail model, which combines the two delivery methods of vehicle delivery and consumer in-store purchase, adds the freshness penalty incurred by fresh agricultural products in the storage process of the prepositioned warehouse, and establishes a mathematical optimisation model of the three-stage logistics network of the prepositioned warehouse that meets the characteristics of omni-channel retailing on the basis of the classical EOQ inventory model. In this work, the shortest delivery time and the smallest total cost are set as the optimisation objectives, and the multi-objective problem is transformed into a single objective through normalisation and linear weighting methods to obtain a mixed-integer optimisation model. This paper solves the problems of site selection for prepositioned warehouses, merchandise replenishment strategies, and optimisation of delivery routes based on data from real cases. Additionally, through sensitivity analysis, the management inspiration of the enterprise is obtained.

Straw Logistics Network Optimization Considering Cost Importance and Carbon Emission under the Concept of Sustainable Development

As biomass power generation projects progress, the supply chain of biomass resources has become a key link for the green development of biomass power facilities. The role of biomass recycling logistics in the sustainable development of biomass resources and power generation endeavors has grown increasingly significant. To realize environmentally friendly and economical straw logistics, it is imperative to establish an efficient, economic and sustainable straw recycling logistics network. Therefore, based on the weighting theory and top-down method, this study proposes a planning model aiming at minimum total cost and minimum carbon emission to locate the logistics network. The immune algorithm is applied to solve and analyze the proposed examples. It is concluded that under the condition that the total cost is reasonable, reducing transportation cost. The verification model can enhance the environmental and economic performance of straw logistics networks. From the perspective of theory and practice, we provide ideas for the optimization of relevant biomass logistics networks and promote the realization of low-carbon sustainable development of logistics networks.

Reverse Logistics Network Design for Medical Waste Disposal under the Scenario of Uncertain Proposal Demand

With the development of the healthcare industry, the demand for medical services and protective equipment is boosted, causing the generation rate of infectious medical waste to increase rapidly. Therefore, it is of utmost importance for decision makers to effectively predict the potential risks and propose corresponding solutions. This paper investigates the reverse logistics network optimization for medical waste under the conditions of an uncertain proposal demand. Firstly, a prediction model of medical waste based on the SEIR epidemiological dynamics is constructed, in which both routine and public health emergency scenarios are simultaneously considered. Secondly, a bi-objective location-routing optimization model for a medical waste reverse logistics network is proposed, by simultaneously optimizing the total economic cost and potential risk throughout the entire logistics process. Subsequently, an NSGA-II algorithm is designed for a model solution in response to the model’s characteristics. The epidemiological dynamics-based prediction model is validated by the real case to be scientifically effective in predicting the amount of generated medical waste with a mean absolute percentage error (MAPE) of 18.08%. The constructed reverse logistics network model and the NSGA II algorithm provide a medical waste process center location, transportation routing, and vehicle selection solutions for both routine and emergency public health cases of Xi’an city with large, medium, and small scales. The above results indicate that the research scheme proposed in this paper could significantly reduce the medical waste logistics-related risks and costs and provide decision makers with more safe and reliable logistical solutions.

E-Commerce Logistics and Supply Chain Network Optimization for Cross-Border

E-Commerce Logistics and Supply Chain Network Optimization for Cross-Border

Research on Cargo Volume Prediction and Adjustment Strategy of Logistics Network Based on Deep Learning and Optimisation Algorithm

Despite existing studies discussing logistics volume forecasting and logistics network optimization, dynamically adjusting the logistics network structure and evaluating the importance of logistics sites and routes during emergencies remains challenging. Consequently, this study aims to develop a line volume prediction model to forecast the volume at each logistics site and route in the future. Building on this, a mathematical model is constructed to determine how to adjust the logistics network when a logistics site is deactivated, thereby reducing operational costs and enhancing efficiency. This paper tackles the issues of logistics site and route volume prediction, allocation, and network restructuring by developing prediction and optimization models. Initially, we utilize the Long Short-Term Memory (LSTM) neural network to create a route cargo volume prediction model, forecasting the route cargo volume for the upcoming month and providing prediction results for three routes: DC14→DC10, DC20→DC35, and DC25→DC62. Subsequently, a linear programming model based on the simulated annealing algorithm is formulated to address the cargo volume allocation following the closure of logistics site DC5. Finally, we establish a logistics network optimization model using the particle swarm optimization algorithm to dynamically adjust the logistics network structure.

Мathematical model of the problem of optimizing logistics networks under conditions of interval determination of input data

Problem. In the conditions of rapid changes in demand and supply in transportation markets, there is a need for corresponding changes in logistics technologies and networks, which are carried out through their reengineering. Existing mathematical models for the optimization of logistics networks are designed for conditions with point-wise, clearly defined input data, which does not allow obtaining solutions resistant to changes in the external environment. This determined the relevance of the scientific and applied task of developing mathematical models of multi-criteria optimization problems of logistics networks for the conditions of interval submission of input data. Goal. The goal is to increase the efficiency of the logistics network optimization technology at the stage of re-engineering by developing a mathematical model of the multi-criteria optimization problem for the conditions of interval submission of input data. Methodology. According to the results of the decomposition of the problem of system optimization of logistics networks as the most complex defined task of their structural and topological optimization. When developing the model, the methodology of system design of territorially distributed objects, methods of multi-criteria optimization, theories of utility and decision-making were used. The apparatus of interval mathematics was used to compare solution options with vaguely specified input data. The results. The result are the formulated and completed formalization of the task of optimizing logistics networks as territorially distributed objects. The relationship for the objective function and constraints of the optimization task of topological structures of centralized three-level logistics networks is proposed. Originality. A mathematical model of the task of reengineering topological structures of centralized three-level logistics networks according to cost and efficiency indicators for interval defined input data and values of local criteria using comparison indices based on the Hukuhara difference has been developed. Practical value. The obtained results make it possible to increase the reliability of optimization results in the processes of design, development planning and reengineering of logistics networks, to obtain variants of the construction of their topological structures that are resistant to changes in external conditions.

Optimisation of multi-level logistics network for agricultural products under community group buying model

This paper introduces a rapidly developing new online retail model, community group buying, and proposes a three-level agricultural logistics network optimisation model. Under the community group buysing model, it is necessary to use different types of vehicles for transportation of agricultural products with different temperature control requirements. The study establishes a multi-objective mixed integer programming model with the objectives of shortest transportation time and minimum total cost, taking into account the freshness penalty cost incurred during transport. The multi-objective problem is transformed into a single objective by normalisation and weighting methods. According to the calculation for the actual case, this paper solves the problems of community group buying grid warehouse location, multiple vehicles use strategy, loading capacity, transportation path optimisation and self-pickup station demand allocation. In addition, through sensitivity analysis, the management insights of community group buying enterprises are obtained: (1) The community group buying enterprises should use brokers of the community group buying model to enhance customer stickiness; (2) The enterprises should focus on developing business in less developed regions; (3) The enterprises need to adjust the proportion of time efficiency and logistics costs according to the real situation.

Retracted: Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Retracted: Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Research on Optimization of Medical Waste Emergency Disposal Transportation Network for Public Health Emergencies in the Context of Intelligent Transportation

In order to build a more comprehensive emergency disposal and transportation network system for medical waste, it is necessary to consider various uncertain factors and data characteristics. Therefore, in the context of intelligent transportation, this article considers the uncertainty of the quantity and regional population density of infectious medical waste generation as well as the emergency disposal of infectious medical waste under multi-cycle and multi-objective conditions, and it constructs a multi-cycle emergency disposal logistics network optimization model for infectious medical waste under uncertain conditions. Through deterministic transformation of the model and data mining of the medical waste disposal logistics network in Wuhan, China, the multi-objective model under uncertain conditions was also solved and sensitivity analyzed using the MOPSO-NSGA2 intelligent algorithm, verifying the effectiveness and superiority of the algorithm.

Optimization of multipath cold-chain logistics network

Optimization of multipath cold-chain logistics network

Research On Emergency Parcel Transfer and Structure Optimization of E-Commerce Logistics Network Based on Multi-Objective Planning

This paper addresses the problem of urgent forwarding and structural optimization of parcels in e-commerce logistics networks. Firstly, based on the historical data of past freight volumes of different routes, this paper predicts the freight volume forecast data of each route by establishing an ARIMA time series forecast model; secondly, a multi-objective optimization model based on genetic algorithm is established to derive the optimal freight volume allocation scheme after the disappearance of route DC5; again, a multi-objective optimization model based on bat algorithm is established to derive the DC9 route Finally, a multi-objective optimization model based on the bat algorithm was developed to derive the route adjustment and cargo allocation scheme after the disappearance of route DC9. This paper concludes that after the cancellation of the DC5 route, the number of routes that are not in normal operation is 23 and the number of logistics paths that are allocated to new cargo is 56 in order to achieve the most balanced route load possible; after the closure of the DC9 route, 21 new roads are opened and 15 roads are closed, which are in a normal flow state and the transhipment is balanced. This paper has more far-reaching applications for multi-objective large-scale NP problems by establishing a multi-objective optimization model based on a heuristic algorithm, which can reduce the solution time of the calculation.

중국 자동차 산업의 역물류 네트워크 최적화에 관한 연구

Reverse logistics network design is a strategic level of decision-making, and the recovery process of abandoned vehicles is inseparable from the support of a complete reverse logistics network. Against the backdrop of the green economy and the circular economy, this study designed a waste vehicle reverse logistics network under two constraints: carbon tax policy and carbon transaction market policy, respectively, and established a multi-purpose mixed integer linear plan model to minimize carbon emissions and costs. In addition, using a Chinese automobile manufacturer as an example, the results of the model of maximizing economic effects (i.e., minimizing costs) and maximizing environmental effects by conducting case verification and using lingo 11.0 are as follows. First, the cost of transportation using pure electric vehicles under the same carbon emission policy is lower than using fuel cars. Second, under the two carbon policies, carbon trading policies have a better emission reduction effect and lower network operating costs. Third, we found that transactional carbon constraints help companies reduce costs and reduce carbon emissions, and help shape long-term, even image-oriented, corporate behavior. By analyzing the optimization of China's waste vehicle reverse logistics network, this study promotes the sustainable and sound development of Chinese waste vehicle recovery companies and realizes the double benefits of the economic environment. There is a certain significance in the research and practice of developing reverse logistics activities in academia

Optimization of reverse logistics network for medical waste recycling

Optimization of reverse logistics network for medical waste recycling

Multi-objective combinatorial optimization analysis of the recycling of retired new energy electric vehicle power batteries in a sustainable dynamic reverse logistics network.

The recycling of retired new energy vehicle power batteries produces economic benefits and promotes the sustainable development of environment and society. However, few attentions have been paid to the design and optimization of sustainable reverse logistics network for the recycling of retired power batteries. To this end, we develop a six-level sustainable dynamic reverse logistics network model from the perspectives of economy, environment, and society. We solve the multi-objective combinatorial optimization model to explore the layout of the sustainable reverse logistics network for retired new energy vehicle power batteries recycling. A case study is implemented to verify the effectiveness of the proposed model. The results show that (a) the facility nodes near the front of the network fluctuate more by opening and closing; (b) the dynamic reverse logistics network is superior to its static counterpart; and (c) cooperation cost changes affect the transaction volume between third-party and cooperative enterprises and total network cost.

Emergency Parcel Dispatching and Structure Optimization of E-Commerce Logistics Network Based on CCNSGA-II

Emergency Parcel Dispatching and Structure Optimization of E-Commerce Logistics Network Based on CCNSGA-II

Emergency Routing and Structural Optimization of E-commerce Logistics Network for Parcel Transportation Based on Multiple Models

Emergency Routing and Structural Optimization of E-commerce Logistics Network for Parcel Transportation Based on Multiple Models

Research on layout optimization of logistics network of metropolitan area based on hub-and-spoke theory

In order to give full play to the role of regional logistics in the regional economic development of the metropolitan area, a kind of hub-and-spoke regional logistics network based on hub-and-spoke model was established, which has the characteristics of hub-and-spoke network scale economy, scope economy, density economy and structure economy. Seventeen technical and economic indicators are sorted out from regional economy, industrial and commercial development, transportation infrastructure development and logistics industry development, and 35 counties and districts in the Capital metropolitan area are used as the research objects in 2020. The model is used to determine the network layout among node cities and to optimize the logistics network in the Capital metropolitan area.

Optimization of sustainable reverse logistics network with multi-objectives under uncertainty

Optimization of sustainable reverse logistics network with multi-objectives under uncertainty