Spatial Structure of China's E-commerce Express Logistics Network Based on Space of Flows

The intermediate link compression characteristics of e-commerce express logistics ne tworks influence the tradition al mode of circulation of goods and economic organization,and alter the city spatial pattern.Based on the theory of space of flows,this study adopts China Smart Logistics Network relational data to build China's e-commerce express logistics network and explore its spatial structure characteristics through social network analysis(SNA),the PageRank technique,and geospatial methods.The results are as follows:the network density is 0.9270,which is close to 1;hence,indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure,thereby eliminating fragmented spaces.Moreover,the average minimum number of edges is 1.1375,which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements.A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights.A diamond-structured network was formed with Shanghai,Guangzhou,Chongqing,and Beijing as the four core nodes.Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China,revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern.This study enriches the theory of urban networks,reveals the flow laws of modern logistics elements,and encourages coordinated development of urban logistics.

Integrated logistics facilities network design for 3PLS under uncertainty

According to the operational characteristics of the logistics networks for the third party logistics supplier （3PLS）, the forward and reverse logistics networks together for 3PLS under the uncertain environment are designed. First, a fuzzy model is proposed by taking multiple customers, multiple commodities, capacitated facility location and integrated logistics facility layout into account. In the model, the fuzzy customer demands and transportation rates are illustrated by triangular fuzzy numbers. Secondly, the fuzzy model is converted into a crisp model by applying fuzzy chance constrained theory and possibility theory, and one hybrid genetic algorithm is designed for the crisp model. Finally, two different examples are designed to illustrate that the model and solution discussed are valid.

Facility location model for a remanufacturing logistics network

First a remanufactming logistics network is con- structed, in which the structure of both the forward logistics and the reverse logistics are of two levels and all the logistics facilities are capacitated. Both the remanufactming products and the new products can be used to meet the demands of customers. Moreover, it is assumed that homogeneous facilities can be designed together into integrated ones, based on which a mixed integer nonlinear programming （MINLP） facility location model of the remanufacturing logistics network with six types of facilities to be sited is built. Then an algorithm based on enumeration for the model is given. The feasible combinations of binary variables are searched by enumeration, and the remaining sub-problems are solved by the LP solver. Finally, the validities of the model and the algorithm are illustrated by means of an example. The result of the sensitivity analysis of parameters indicates that the integration of homogeneous facilities may influence the optimal solution of the problem to a certain degree.

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

MODELING AND ROBUST DESIGN OF REMANUFACTURING LOGISTICS NETWORKS BASED ON DESIGN OF EXPERIMENT

The uncertainty of time, quantity and quality of recycling products leads tothe bad stability and flexibility of remanufacturing logistics networks, and general design onlycovered the minimizing logistics cost, thus, robust design is presented here to solve theuncertainty. The mathematical model of remanufacturing logistics networks is built based onstochastic distribution of uncontrollable factors, and robust objectives are presented. Theintegration of mathematical simulation and design of experiment method is performed to do sensitiveanalysis. The influence of each factor and level on the system is investigated, and the main factorsand optimum combination are studied. The numbers of factors, level of each factor and designprocess of experiment are investigated as well. Finally, the process of robust design based ondesign of experiment is demonstrated by a detailed example.

Modeling of Robust Design of Remanufacturing Logistics Networks

The uncertainty of time, quantity and quality of recycling products leads to the bad stability and flexibility of remanufacturing logistics networks, while general design only covers the minimizing logistics cost, so robust design is presented to solve it. The mathematical model of remanufacturing logistics networks is built on the stochastic distribution of uncontrollable factors, and robust objectives are presented. The basic elements of robust design of remanufacturing logistics are redefined, and each part of mathematical model is explained in detail as well. Robust design of remanufacturing logistics networks is a problem of multi-objective optimization in essence.

Obtain the optimal of logistics delivery network with annealing algorithm

Simulated annealing(SA) algorithm is a heuristic algorithm,proposed one approximation algorithm of solving optimization combinatorial problems inspired by objects in the annealing process of heating crunch. The algorithm is superior to the traditional greedy algorithm,which avoids falling into local optimum and reaches global optimum. There are often some problems to find the shortest path,etc in the logistics and distribution network, and we need optimization for logistics and distribution path in order to achieve the shortest,best,most economical,and so on. The paper uses an example of SA algorithm validation to verify it,and the method is proved to be feasible.

The Preliminary Study on the Performance Appraisement about the Logistics Network Organization

How the performance in the course of implementing the logistics network organization is, and how the benefit level is produced, are undoubtedly focuses that cooperative parties pay close attention to, and the key to the network organization, too. The research on the performance appraisement about the network organization is not only very necessary, but also very important. This paper describes the characteristics of the performance appraisement about the logistics network organization, and sets up the evaluation index through analyzing the principle of constituting the logistics network organization＇s performance index system.

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).

An Efficient Cyber Security and Intrusion Detection System Using CRSR with PXORP-ECC and LTH-CNN

Intrusion Detection System(IDS)is a network security mechanism that analyses all users’and applications’traffic and detectsmalicious activities in real-time.The existing IDSmethods suffer fromlower accuracy and lack the required level of security to prevent sophisticated attacks.This problem can result in the system being vulnerable to attacks,which can lead to the loss of sensitive data and potential system failure.Therefore,this paper proposes an Intrusion Detection System using Logistic Tanh-based Convolutional Neural Network Classification(LTH-CNN).Here,the Correlation Coefficient based Mayfly Optimization(CC-MA)algorithm is used to extract the input characteristics for the IDS from the input data.Then,the optimized features are utilized by the LTH-CNN,which returns the attacked and non-attacked data.After that,the attacked data is stored in the log file and non-attacked data is mapped to the cyber security and data security phases.To prevent the system from cyber-attack,the Source and Destination IP address is converted into a complex binary format named 1’s Complement Reverse Shift Right(CRSR),where,in the data security phase the sensed data is converted into an encrypted format using Senders Public key Exclusive OR Receivers Public Key-Elliptic Curve Cryptography(PXORP-ECC)Algorithm to improve the data security.TheNetwork Security Laboratory-Knowledge Discovery inDatabases(NSLKDD)dataset and real-time sensor are used to train and evaluate the proposed LTH-CNN.The suggested model is evaluated based on accuracy,sensitivity,and specificity,which outperformed the existing IDS methods,according to the results of the experiments.

Strategy Choices in Logistic Enterprises： Porter＇s View vs Network Approach

Compared with traditional enterprises, strategy choice and implementation for logistic enterprises has its particularity. This paper discusses character of logistic enterprises and analyzes the different genres of strategy, and then the paper introduces the choice of strategy based on network approach. Finally, the authors explain how to ensure the programming and implementation of strategy from different point of view such as financial perspective, client perspective, procedure perspective, internal and organizational learning perspective.

Two-stage stochastic programming with robust constraints for the logistics network post-disruption response strategy optimization

Logistics networks (LNs) are essential for the transportation and distribution of goods or services from suppliers to consumers. However, LNs with complex structures are more vulnerable to disruptions due to natural disasters and accidents. To address the LN post-disruption response strategy optimization problem, this study proposes a novel two-stage stochastic programming model with robust delivery time constraints. The proposed model jointly optimizes the new-line-opening and rerouting decisions in the face of uncertain transport demands and transportation times. To enhance the robustness of the response strategy obtained, the conditional value at risk (CVaR) criterion is utilized to reduce the operational risk, and robust constraints based on the scenario-based uncertainty sets are proposed to guarantee the delivery time requirement. An equivalent tractable mixed-integer linear programming reformulation is further derived by linearizing the CVaR objective function and dualizing the infinite number of robust constraints into finite ones. A case study based on the practical operations of the JD LN is conducted to validate the practical significance of the proposed model. A comparison with the rerouting strategy and two benchmark models demonstrates the superiority of the proposed model in terms of operational cost, delivery time, and loading rate.

Towards understanding network topology and robustness of logistics systems

Advanced integration of logistics systems has been promoted for competitiveness and sustainability.Interconnection of transport operations increases complexity at a network level,which reduces the predictability of the response of the system to disruptions.However,our understanding of the behavior of such systems is still limited.In particular,the topology of the network,which changes as the systems are integrated,is an important factor that affects the performance of the entire system.Knowledge of such mechanisms would be useful in the design and evaluation of integrated logistics.Here,we developed a simple simulation framework for logistics networks that extracts the essence of the problem.We performed extensive numerical experiments for three scenarios that mimic changes in demand:(i)locally and temporally increased traffic demand,(ii)globally and temporally increased traffic demand,and(iii)permanent change in demand pattern,under various conditions on the type of route-finding algorithm,network structure,and transportation capacity.Adaptive route-finding algorithms were more effective in square lattice and random networks,which contained many bypass routes,than in hub-andspoke networks.Furthermore,the square lattice and random networks were robust to the change in the demand.We suggest that such preferable properties are only present in networks with redundancy and that the bypass structure is an important criterion for designing network logistics.We also performed a realistic case study that mimics interregional truck transport in Japan and confirmed that our conclusions are applicable to a practical problem.

Dry Port-Seaport Logistics Network Construction under the Belt and Road Initiative: A Case of Shandong Province in China

In recent years,China's dry ports have entered into a period of rapid development,especially driven by the Belt and Road initiative(BRI).This initiative not only provides valuable opportunities,but also intensifies fierce competition between ports.In order to earn more profits and maintain an advantageous position,dry ports generally tend to rely on seaports to increase competitiveness and attract more goods,and seaports are also willing to cooperate with dry ports to expand their business.As a large coastal province in China,Shandong Province has good maritime resources.Because of the fierce competition among seaports inside and outside Shandong Province,port operators should make good use of the opportunity offered by BRI to make connections with the inland cities through the dry port-seaport logistics network and enhance the competitiveness.In order to take an active part in the process of the BRI,forming a dry port-seaport logistics network is a win-win strategy for Shandong province.The research first analyzes the impact of the Belt and Road initiative on ports of Shandong and its development,then uses complex network theory and TOPSIS method to select dry port candidate cities from BRI's important transportation nodes.After considering economic benefits,carbon emissions and construction costs,a multi-objective optimization model is established with a construction cost preference coefficient.Then the NSGA-II algorithm is used to solve the realistic problem.The study finds that when the construction cost increases,the transportation cost and carbon emission cost will decrease,which indicates that the dry port-seaport logistics network established under the BRI can reduce the cost of logistics transportation and environmental pollution.

Research on Logistics Network Infrastructures Based on DEA-PCA Approach:Evidence from the Yangtze River Delta Region in China

Compared with the extensive research on logistics network infrastructures(LNIs)in the developed world,empirical research is still scarce in China.In this paper the theory of LNIs is firstly overviewed.Then a new evaluation index system for LNIs is set up which contains factors that reflect the economic development level,transportation accessibility and turnover volume of freight traffc.An empirical study is carried out by using data envelopment analysis(DEA)and principal component analysis(PCA)approach to classify LNIs into 4 clusters for 25 cities in the Yangtze River Delta Region of China.According to the characteristics of the 4 clusters,suggestions are proposed for improving their LNIs.Finally,after comparing different LNIs of 25 cities in the Yangtze River Delta Region of China,this paper proposes that different LNIs including hub,central distribution center or cross docking center,regional distribution center or distribution center should be built reasonably in order to meet the customer's requirement in the four different cluster cities.

Application of Integrated Multiple Criteria Data Envelopment Analysis to Humanitarian Logistics Network Design

This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.

Taguchi Analysis for Improving Optimization of Integrated Forward/Reverse Logistics

The distribution–allocation problem is known as one of the most comprehensive strategic decisions.In real-world cases,it is impossible to solve a distribution–allocation problem completely in acceptable time.This forces the researchers to develop efficient heuristic techniques for the large-term operation of the whole supply chain.These techniques provide near optimal solution and are comparably fast particularly for large-scale test problems.This paper presents an integrated supply chain model which is flexible in the delivery path.As solution methodology,we apply a memetic algorithm with a novelty in population presentation.To identify the optimum operating condition of the proposed memetic algorithm,Taguchi method is adopted.In this study,four factors,namely population size,crossover rate,local search iteration and number of iteration,are considered.Determining the best level of the considered parameters is the outlook of this research.

Logistics Network Design for Manufacturing Enterprises with Component Processing Workshops

Logistics network design influences the efficiency and cost of Logistics directly.Some manufacturing enterprises not only have warehouse hubs,but also build component processing workshops which are usually located in those places where the costs of materials and workforce are lower.This paper establishes a logistics network design model for the manufacturing enterprises with component processing workshops based on 0-1 mixture integer programming.The model optimizes the logistics network in an integrated view,by which the selection of the nodes,the manufacturing plan,and transportation plan can be obtained.An example is given to verify its feasibility.The approach is helpful for designing of the logistics network in manufacturing enterprises.

Application of Transformed Two-Stage Network DEA to Strategic Design of Biofuel Supply Chain Network

This paper proposes an innovative procedure for designing efficient biomass-biofuel logistics networks(BBLNs).This procedure is based on the two-stage network data envelopment analysis(TSN-DEA)models that have been developed to provide specific process guidance for the managers to improve the efficiency of the decision-making unit(DMU)with the TSN process.The crucial issue of the TSN-DEA is that the overall efficiency score depends on the DMUs under evaluation.Thus,the rankings for the DMUs generated by the TSN-DEA model are inconsistent.As a result,the TSN-DEA-based ranking methods are limited.The TSN-DEA’s inconsistency frequently makes it difficult for decision-makers to select the top-rated DMUs.We develop the transformed TSN(T-TSN)DEA method by applying the multi-criteria DEA model to overcome this issue.The proposed method transforms the DMUs with any number of inputs,intermediate measures,and outputs in the TSN process,through the multi-objective programming model with a minimax objective approach,into the DMUs with two inputs and one output in the single-stage network(SSN)process.Then,the well-known DEA methods for the SSN,such as the cross-efficiency and super-efficiency DEA methods,can be applied to evaluate and rank the transformed DMUs more consistently.We exhibit the applicability of the proposed approach for the BBLN design problem.A case study of South Carolina in the USA demonstrates that the proposed method performs well in identifying efficient BBLN schemes more consistently than the traditional TSN-DEA.

A dynamic logistic regression for network link prediction

In social network analysis, link prediction is a problem of fundamental importance. How to conduct a comprehensive and principled link prediction, by taking various network structure information into consideration,is of great interest. To this end, we propose here a dynamic logistic regression method. Specifically, we assume that one has observed a time series of network structure. Then the proposed model dynamically predicts future links by studying the network structure in the past. To estimate the model, we find that the standard maximum likelihood estimation(MLE) is computationally forbidden. To solve the problem, we introduce a novel conditional maximum likelihood estimation(CMLE) method, which is computationally feasible for large-scale networks. We demonstrate the performance of the proposed method by extensive numerical studies.