Logistics Network Optimization Research Articles

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

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

Emergency logistics network optimization with time window assignment

During natural disasters or accidents, an emergency logistics network aims to ensure the distribution of relief supplies to victims in time and efficiently. When the coronavirus disease 2019 (COVID-19) emerged, the government closed the outbreak areas to control the risk of transmission. The closed areas were divided into high-risk and middle-/low-risk areas, and travel restrictions were enforced in the different risk areas. The distribution of daily essential supplies to residents in the closed areas became a major challenge for the government. This study introduces a new variant of the vehicle routing problem with travel restrictions in closed areas called the two-echelon emergency vehicle routing problem with time window assignment (2E-EVRPTWA). 2E-EVRPTWA involves transporting goods from distribution centers (DCs) to satellites in high-risk areas in the first echelon and delivering goods from DCs or satellites to customers in the second echelon. Vehicle sharing and time window assignment (TWA) strategies are applied to optimize the transportation resource configuration and improve the operational efficiency of the emergency logistics network. A tri-objective mathematical model for 2E-EVRPTWA is also constructed to minimize the total operating cost, total delivery time, and number of vehicles. A multi-objective adaptive large neighborhood search with split algorithm (MOALNS-SA) is proposed to obtain the Pareto optimal solution for 2E-EVRPTWA. The split algorithm (SA) calculates the objective values associated with each solution and assigns multiple trips to shared vehicles. A non-dominated sorting strategy is used to retain the optimal labels obtained with the SA algorithm and evaluate the quality of the multi-objective solution. The TWA strategy embedded in MOALNS-SA assigns appropriate candidate time windows to customers. The proposed MOALNS-SA produces results that are comparable with the CPLEX solver and those of the self-learning non-dominated sorting genetic algorithm-II, multi-objective ant colony algorithm, and multi-objective particle swarm optimization algorithm for 2E-EVRPTWA. A real-world COVID-19 case study from Chongqing City, China, is performed to test the performance of the proposed model and algorithm. This study helps the government and logistics enterprises design an efficient, collaborative, emergency logistics network, and promote the healthy and sustainable development of cities.

Sustainable Logistics Network Optimization From Dry Ports to Seaport: A Case Study From Pakistan

Several considerations are explored in each mode of transportation for the safe, quick, and environmentally friendly movement of goods. To obtain the advantages in all transportation modes, it is critical to develop appropriate models and algorithms. By expanding our understanding of the planning of bi-objective optimization problems, this study contributes to the field of real-time green logistics analysis. The paper provides case studies based on road and road-rail transportation from dry ports to a seaport in Pakistan. Analysis of the cases shapes the economic and environmental planning of transport. Because there is little research on this topic in Pakistan, the innovative aspect is to reduce the cost and greenhouse gas (GHG) emissions of road and intermodal freight transportation between dry ports and seaport. A mixed-integer linear programming model is used for the formulation of the bi-objective problem. Pareto front solutions are provided to trade-off the cost and GHG emissions in delivering goods from dry ports to seaport in Pakistan. The study uses real-life data from one of the largest logistics service providers in Pakistan. Results show that intermodal transportation is 82.6% more economical and 78% greener compared with road freight transportation. Further, this study could be extended by including other factors such as noise, air pollution, and traffic accidents.

B2C e-commerce logistics network optimization model

In this paper, considering the characteristics of e-commerce logistics and the problems arising from the construction of logistics network, based on the full investigation and research of the B2C electricity supplier operation mode, we have studied and summarized the research results of scholars at home and abroad aiming at the related problems, and summarized and summarized the methods and steps of logistics network optimization in the whole country. First, we established the logistics network structure.The definition of network level, node function and connection between nodes is carried out. Then, through the improved urban agglomeration order gravity model, the scope of self logistics city is screened. Finally, the link of logistics network structure is scheduled for completion with the goal of cost optimization.

Designing a Reverse Logistics Network Model for Waste Batteries

The logistics industry plays an important role in circular economy. Therefore, not only economic benefits, but also environmental protection factors have to be considered in reverse logistics. This paper uses the multi-objective 0-1 mixed integer programming to establish a reverse logistics network optimization model for waste batteries. The objective function is to minimize both, logistics costs and carbon dioxide emissions. The model considers the basic settings of reverse logistics (including recycling nodes, manufacturing, and processing nodes) and the material flow between different settings. In solving the model, Lingo 14.0 is used in this paper. An actual case of a waste battery reverse logistics enterprise verifies the effectiveness of the model in this paper. The results show that the application of this model can effectively improve the operating efficiency of waste battery reverse logistics enterprises.

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

E-commerce and logistics are symbioses with each other, but cross-border e-commerce (CBEC) still cannot break away from cross-border logistics. With the progress of economic internationalization, economic and trade ties around the world have become closer and closer, and the level of international business exchanges has been improved. The rise of multinational e-commerce has also caused unprecedented difficulties to multinational logistics and supply chain management. The application of deep neural networks in various fields provides opportunities for cross-border e-commerce platforms to solve these problems. The existing logistics distribution model cannot keep up with the development of CBEC and has become a constraint and bottleneck for the development of CBEC. Therefore, this article introduces deep learning neural network to cross-border logistics and supply chain based on the analysis of the existing cross-border logistics model and supply chain model and the status quo of e-commerce development. It optimizes the existing cross-border logistics and supply chain network in order to break through the current bottleneck in the development of CBEC. This paper shows through research that introducing deep learning neural networks into CBEC logistics and supply chain can improve the efficiency of logistics and supply chain. Compared with the previous efficiency, the efficiency of network optimization can be increased to about 50%, reducing the cost of cross-border logistics and supply chain. The research in this article has great theoretical and guiding significance for the development of CBEC.

Site Selection Optimization of Reverse Logistics Network for Waste Tires

In order to solve the problem of reverse recycling of waste tires in Heilongjiang Province, this paper chooses the third party as the core to construct a reverse logistics network system of waste tires based on the current situation of reverse logistics of waste tires. The reverse recycling area of waste tires in Heilongjiang Province is divided into five areas (the first area is Harbin; the second area contains Qiqihar, Daqing, and Suihua; the third area contains Yichun, Hegang, Jiamusi, and Shuangyashan; Qitaihe, Jixi, and Mudanjiang form the fourth area; and the fifth area contains Daxinganling and Heihe). The analytic hierarchy process (AHP) is employed to analyze the influence factors of site selection of reverse logistics network and obtain the total weight of each evaluation factor. The weights of economic conditions, the number of waste tires, traffic conditions, development planning and policy, and geographical conditions are obtained as 0.3547, 0.2256, 0.1690, 0.1644, and 0.0863, respectively. The economic conditions and the number of waste tires with high weights are vital factors for selecting a reverse logistics network for waste tires. The linear mixed-integer programming method (LINGO) is utilized for site selection. Harbin, Qiqihar, Daqing, Mudanjiang, Jiamusi, and Suihua are chosen for the recovery center’s site selection, while Daqing, Mudanjiang, and Suihua are chosen as the site selection of remanufacturing enterprise.

Optimization of the distribution logistics network: a case study of the metalworking industry in Colombia

Logistics management is a key factor for business competitiveness because of the variety of strategies available to improve the distribution of goods through the supply chain, enabling the optimization of the resources assigned to this effect. A key aspect for good logistics management is the distribution network, where the location of the network components plays a key role, especially in the case of distribution centers, which are platforms through which the goods received from factories or suppliers are redistributed to the various points of sale. In the above context, this case study proposes a solution for selecting two locations from among four possible sites for construction of distribution centers for a company in the metalworking industry, aimed at minimizing operating costs through the design of a logistics distribution network, using as a tool the GUSEK software. To this effect, the aspects taken into consideration include vehicle capacity, the costs associated with opening a distribution center, types and volume of the products to be shipped, costs associated with the travel distances, the production capacity of the factories, and customer demand, among others. Execution of the model produces the best locations for the distribution centers and the types of vehicles to be used based on their capacity and the optimal routes for transporting a company’s goods.

Modelling and optimisation of reverse logistics network under fuzzy environment

Modelling and optimisation of reverse logistics network under fuzzy environment

Modelling and optimization of reverse logistics network under fuzzy environment

Modelling and optimization of reverse logistics network under fuzzy environment

An Optimization Model of Reverse Logistics Network Design

With the increasing development of China’s economy, product and materials of reverse logistics is also increasing. Reverse logistics network design is of great significance to reduce cost of reverse logistics enterprises and society. In this paper, 0-1 mixed integer programming is used to establish a reverse logistics network optimization model which takes into account establishment of fixed facilities and flow between different logistics nodes. The objective function is profit maximization, and the constraints contain the processing capacity of facilities vehicle loading capacity. Lingo 14.0 is used to solve the model. The results show that the application of the model can improve the profits of reverse logistics enterprises on the basis of optimizing logistics facility allocation and material flow.

MATHEMATICAL MODELS OF DECISION SUPPORT IN THE PROBLEMS OF LOGISTICS NETWORKS OPTIMIZATION

The subject of research in the article is the process of decision support in the problems of logistics networks optimization. The goal of the work is to develop a set of mathematical models of logistics network optimization problems to increase the efficiency of decision support systems by coordinating the interaction between automatic and interactive procedures of computer-aided design systems. The following tasks are solved in the article: review and analysis of the current state of the problem of decision support in the problems of logistics networks optimization; decomposition of the problem of decision support for the optimization of logistics networks; development of a mathematical model of the general problem of network optimization in terms of economy, efficiency, reliability and survivability; development of a set of technological mathematical models for the correct reduction of many effective options for building logistics networks for the final choice, taking into account difficult to formalize factors, knowledge and experience of the decision maker (DM). The following methods are used: systems theory, utility theory, optimization and operations research. Results. Analysis of the current state of the problem of logistics networks optimization has established the existence of the problem of correct reduction of a subset of effective options for their construction for ranking, taking into account difficult to formalize factors, as well as knowledge and experience of DM. The decomposition of the problem into tasks is performed: definition of the principles of network construction; network structure selection; determination of the topology of network elements; choice of network operation technology; determination of parameters of elements and communications (means of cargo delivery); multi criteria evaluation and selection of the best option for building a network. A mathematical model of the general problem of network optimization in terms of economy, efficiency, reliability and survivability is proposed. To coordinate the interaction between automatic and interactive network optimization procedures, it is proposed to use a combined method of ranking options, which allows you to identify and correctly reduce the subset of effective options for ranking DM. To implement the method, mathematical models of problems of the procedure of ranking options in the technologies of project decision support have been developed, which allow to combine the advantages of the technologies of the ordinalistic and cardinalistic approaches. Conclusions. The developed set of mathematical models expands the methodological bases of automation of processes of support of multi criteria decisions on optimization of logistic networks, allows to carry out correct reduction of set of effective options of their construction for the final choice taking into account factors, knowledge and experience of DM. The practical use of the proposed models and procedures will reduce the time and capacity complexity of decision support technologies, and through the use of the proposed selection procedures - to improve their quality across a variety of functional and cost indicators.

B2C E-Commerce Logistics Network Optimization Model

In this paper, considering the characteristics of e-commerce logistics and the problems arising from the construction of logistics network, based on the full investigation and research of the B2C electricity supplier operation mode, we have studied and summarized the research results of scholars at home and abroad aiming at the related problems, and summarized and summarized the methods and steps of logistics network optimization in the whole country. First, we established the logistics network structure.The definition of network level, node function and connection between nodes is carried out. Then, through the improved urban agglomeration order gravity model, the scope of self logistics city is screened. Finally, the link of logistics network structure is scheduled for completion with the goal of cost optimization.

A Multi Logistics Network Optimization Model of Power System based on Stochastic Demand and Inventory Decision

According to the disposal demand for packets and all kinds of constraints in the current condition, this paper discusses a modeling method of extended double-layer capacitated arc routing problems with Capacitated Arc Routing Problem (CARP) optimization model based on express logistics. The model is described in detail, and the solution of the model is discussed. The paper analyses and discusses the solution to complexity of the model, and proposes a better solution to the double-layer CARP optimization model. According to the scheme, the paper chooses a sort of improved ant colony algorithm to solve the model. And the results show that the scheme is beneficial to controlling the cost of logistics links, to minimizing purchase cost, transportation cost and delivery time. The scheme plays a very imperative role in enhancing the competitiveness of enterprises

Optimization of E-commerce Logistics Network in African Countries

The purpose of this research is to assist the Central African’s logistics network authorities in making, evaluating, and realizing their decisions in regard to the development and management of e-commerce logistics network of companies. This article evaluated and used mathematical models which provided a descriptive analysis on the current situation of its’ logistics network while applying the e-commerce logistics network optimization method in dealing with common issues of the logistics network in Central Africa, especially Chad. The suggested network in this study would promote the “from plant-to-from DC” ratio of 83% to 17% which conforms to the companies’ objective in progressing towards direct plant shipments. In regard to that, it was proved that direct plant shipments could reduce the distribution costs from 12% to 3% of the net sales (approximately $135,000 in monthly savings).

Optimization of the cold supply chain logistics network with an environmental dimension

This article is the result of generalizing a real practical problem of optimizing the operation of a cold supply logistics network. A small (up to 100 clients) logistics company solves the problem of operational planning: during the working day (fixed time window) to provide the supply of cold (food) products from distribution centers to end consumers along well-defined routes (i.e., the logistic network graph is fixed). The company has set the following conditions for the authors. In addition to minimizing the usual transport costs, take into account also the environmental costs (associated with negative consequences for the environment) that arise during the operation of the logistics supply network. And also when deciding to use software available to the company. The case is considered when the transport tariff on each route is a linearly increasing function of the total volume of all traffic on this route. When the Nash equilibrium conditions are met, the mathematical model for optimizing the total costs of the logistics network is reduced to a convex (quadratic) programming problem. Computer implementation in MS Excel environment has been carried out. This makes it possible to carry out simulation calculations for various options for transport costs on routes, taking into account environmental costs.

E‐Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm

Based on the problem of e‐commerce logistics and distribution network optimization, this paper summarizes the solution ideas and solutions proposed by domestic and foreign scholars and designs a method to optimize the B2C e‐commerce logistics and distribution network by taking into account the special traffic conditions in the city. The logistics network optimization model is established and solved by combining various methods. Taking into account the new target requirements constantly proposed in the modern logistics environment, the vehicle path problem under the generalized objective function is studied, and the multidimensional impact maximization problem in this type of problem is proposed and modeled. The problem follows from the path planning for emergency material delivery. Given locations, roads, and multiple classes of supplies in a map, each road allows vehicles to deliver each class of supplies with a certain probability. The goal of the problem is how to select a finite number of locations in the map as centers of supplies so that the number of locations that can be effectively covered by vehicle paths from them is maximized with the desired probability. For the first time, we used a hybrid genetic algorithm to optimize the e‐commerce logistics path, and the optimized results are more reasonable than other algorithms.

Research progress on logistics network optimization under low carbon constraints

In this paper, a literature review was conducted on the optimization of logistics network under low carbon constraints. This paper summarized the basic research process of logistics network optimization, and discussed the basic problems of logistics network optimization (distribution center location and vehicle distribution route optimization) and the compound optimization problems of logistics network (forward logistics network optimization and reverse logistics network optimization). In this paper, we mainly discuss the mathematical model constructed by one or more of the goals of minimum carbon emissions, minimum sum of total costs, minimum total delivery time and minimum total delivery distance, and the solving strategies using heuristic algorithms such as particle swarm optimization, genetic algorithm, and ant colony algorithm. It provided the latest technology in this field for the researchers of enterprise logistics network model and points out the future development trend.

Research Framework of Fresh Agricultural Products Logistics Network Optimization Based on Cold Chain

The paper comprehensively integrates multidisciplinary theoretical knowledge such as complexity network, game theory, ecology, system coordination optimization theory, using mathematical analysis and system model construction and other tools to carry out structural analysis and operation mechanism research on agricultural product cold chain logistics ecosystem. The paper explains the interrelationship between the micro-behaviors of the node members of the cold chain system and the evolution of the macro-structure of the system, reveals the complexity of the evolution of the cold chain logistics ecosystem, and studies the impact of the system coordination mechanism on the optimal decision of the system members. The agricultural product cold chain ecosystem network will be comprehensively coordinated and optimized, thereby ultimately improving the overall performance of the cold chain system.

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Globalization opens up new perspectives for handling goods distribution in logistic networks. However, establishing an efficient inventory policy is challenging by virtue of the analytical and computational complexity. In this study, the goods distribution process that was governed by the order-up-to policy, implemented in either a distributed or centralized way, was investigated in the logistic systems with complex interconnection topologies. Uncertain demand may be imposed at any node, not just at conveniently chosen contact points, with a lost-sales assumption that introduces a non-linearity into the node dynamics. In order to adjust the policy parameters, the continuous genetic algorithm (CGA) was applied, with the fitness function incorporating both the operational costs and customer satisfaction level. This study investigated how to select the parameters of the popular inventory management policy when operating in the non-trivial networked structures. Moreover, precise guidelines for the CGA tuning in the considered class of problems were provided and evaluated in extensive numerical experiments.