Complex Logistics Networks Research Articles

Research on Optimization of Power Battery Recycling Logistics Network

With the popularity and development of electric vehicles, the demand for power batteries has increased significantly. Power battery recycling requires a complex and efficient logistics network to ensure that used batteries can be safely and cost-effectively transported to recycling centers and properly processed. This paper constructs a dual-objective mathematical model that minimizes the number of recycling centers and minimizes the logistics cost from the service center to the recycling center, and designs the power battery disassembly and recycling process and the recycling logistics network, and finally uses a genetic algorithm to solve it. Finally, this article takes STZF Company as an example to verify the effectiveness of this method. The verification results show that the logistics intensity of the optimized power battery recycling logistics network has been reduced by 36.2%. The method proposed in this article can provide certain reference for power battery recycling logistics network planning.

Assessing the Development Level of Logistics for Sustainable Cities in Urban Agglomeration Based on a Multi-Layer Complex Network

Evaluating the development level of urban logistics can significantly inform policies for the sustainable development of each city in an urban agglomeration. This study analyzed the logistics development of 11 cities in the Guanzhong Plain urban agglomeration (GPUA) of China. Compared to traditional urban logistics evaluation methods considering individual attributes, this study constructed a multi-layer complex logistics network of urban agglomerations (MCLNUA) based on complex network theory, which takes into account the multiple connections between cities. The development levels of logistics in these cities were evaluated from a multi-dimensional perspective of “point–line–surface”, (the “point” represents the node characteristic index of the city, the “line” represents the strength and direction of urban logistics connections between cities, and the “surface” represents the cohesive subgroup of cities). An urban spatial hierarchy and corresponding spatial development plan for urban logistics were also developed. The results show that there are significant differences in logistics levels between different cities. The spatial structure of the overall network connections shows the pattern of being strong in the south and weak in the north, and strong in the east and weak in the west. There are differences in the strength of connections between cohesive subgroups. The research provides a reference for the sustainable development of regional logistics in other urban agglomerations.

Risk Reduction of Marine Oil Spill using Clusters of Fruit Peel Pellets

Globalization has led to massive rise in cross border trade. Increase in E-commerce business has contributed to this too. As a result, a continuous and complex logistics network of supply chains operate across the globe round the clock. Transportation of goods is the most essential activity of this network. Statistics reveals that approximately 90 percent of world’s goods are transported via sea route. This intense network of shipment poses a huge threat to marine ecosystem in numerous ways. One of the most dangerous events for marine ecosystem is oil spill. Oil spill from vessels and pipelines are a major reason behind mortality of marine wildlife. The present work focuses on developing a cost-effective sustainable solution for mitigation of marine oil spill. It was found from existing literature that peels of some fruits have substantial oil absorbing capacity. This fact was experimentally validated and a reduced scale prototype was designed aiming for the task of deployment in case of oil spill in marine waters. The experimental results show that the proposed model floats on water after absorbing oil up to its saturation value. It was also found that through appropriate mechanical setup, absorbed oil can be extracted for reuse or processing.

Freight Time and Cost Optimization in Complex Logistics Networks

The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to the large number of variables and nonlinear dependencies involved. Here, we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer’s demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. In addition, using customer logistics and thek-means algorithm, we propose additional warehouse locations. For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Controllability Robustness Against Cascading Failure for Complex Logistics Networks Based on Nonlinear Load-Capacity Model

In order to achieve good connectivity after the cascading failure of a logistics network, this paper studies the controllability robustness of complex logistics network based on the nonlinear load-capacity (NLC) model. Firstly, the extended Baraba' si and Albert (BA) network is constructed as a complex logistics network for experiments, based on the power law distribution and the agglomeration and sprawl evolution mechanism. Secondly, the existence of the NLC relationship of the real logistics network is proved, and then the NLC model of complex logistics networks is proposed. Furthermore, a simulation analysis of the controllability robustness and influencing factors of the complex logistics network is carried out under four different cascading failure models. In those models, different scenarios of the NLC and the classical linear load-capacity (LLC) model with initial load (IL)/initial residual capacity (IRC) load-redistribution strategies are combined. The research results show that the main influencing factors of the cascading failure of complex logistics networks for the controllability robustness P' are the tolerance parameters β and γ. Moreover, the effect of γ on the load-capacity relationship under the NLC model is more significant than that of β. Among the four cascading failure models, the one based on the NLC model with IRC strategy is the optimal for controllability robustness. Based on the optimal model, the simulation considering the perspective of the logistics economy shows that the relationship among the network cost e, P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> and γ is as follows: under a fixed cost, the greater is γ, the stronger is P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> . Also, when 2 <; γ ≤ 9, the robustness of the network is controllable. According to the requirements of real logistics networks, both controllability robustness and the logistics cost can be controlled, and a solution that against cascading failure can be obtained by adjusting the minimum residual load.

Controllability Robustness Against Cascading Failure for Complex Logistic Network Based on Dynamic Cascading Failure Model

Inspired by the empirical dynamic characteristics of the load of real logistics network, we propose a dynamic cascading failure model against cascading failure, which is more suitable for complex logistics network by adding dynamic factors based on the nonlinear load-capacity model under initial residual capacity load-redistribution strategy. The simulation is executed on the complex logistics network model and the results show that the controllability robustness and economy after cascading failure based on the dynamic cascading failure model is feasible and effective. It can effectively reduce the logistics cost and enhance controllability robustness against cascading failure by adjusting the network cost $e$ and capacity parameter $\gamma $ , so as to balance the controllability robustness and economy for the complex logistics network.

Business intelligence for service parts logistics management

Many leading companies now offer global customers better spare parts services for system maintenance through a complex service logistics network, which extends traditional on-site stocking management to boost profit margins. The major challenge that spare parts service providers face is how to achieve desired service levels at a low cost and minimise excess inventory in the global spare parts supply chain. To address this issue, we demonstrate an inventory redeployment strategy that transforms a conventional spare parts supply chain into a closed-loop, multi-echelon service network capable of redeploying inventory from overstocked to understocked facilities, and thus reducing purchases of high-value spare parts. To assess the quality of our novel approach, we used a network flow optimisation model to analyse the proposed excess inventory redeployment strategy based on an international company's service parts operations. Significant inventory cost savings were identified.

A Methodological Approach for Development and Deployment of Data Sharing in Complex Organizational Supply and Logistics Networks with Blockchain Technology

Each manufacturer, supplier, and retailer has its own chain of collaborating stakeholders to meet their customer demands. Many perspectives can be taken like food safety, security, and sustainability, which may each lead to separate solutions that are not necessarily interoperable with each other. Data can only be shared within the context of those solutions and only with extra effort, and thus costs, across these solutions. To address this solution, this paper proposes a methodological approach for specification of data that can be shared with rapid deployment by for instance a blockchain based - or a peer-to-peer infrastructure. The methodological approach is based on basic informatics principles like the Turing machine and ontologies. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Capacitated multi-modal network flow models for minimizing total operational cost and CO2e emission

Abstract Green logistics and transportation impose new requirements on distribution planning and flow optimization over complex logistics network. Carbon-dioxide equivalent (CO2e) emission on a road, for instance, depends on the transportation mode and vehicle type selected along the road. The handling cost of a load at a transshipment city also depends on the change of transportation mode and vehicle type from inbound to outbound at the city. Compared with traditional network structure, multi-modal network is characterized by multi-attributes link and dependent transshipment node (in terms of minimizing total cost and emission), which significantly increases problem complexity. This study attempts to address key issues in modeling and analysis of such systems. Analytical models are developed to characterize the problem structure/features explicitly and integrate decisions at single- and multi-objective levels. A set of experiments, designed based on real transportation logistics network, are carried out to verify and validate models’ functions, analyze sensitivity of parameters, and evaluate solution convergence behavior. The results indicated that while the problem is NP-hard, solutions via proper analytical models can be derived efficiently for problems of practical scale.

An Integrated Strategy for Cost Optimization of Reverse Logistics Network Under Uncertain Environment

In uncertain environment, it is very difficult to optimize both cost and performance in complex reverse logistics network. This paper develops an integrated strategy to solve the cost optimization problem in reverse logistics network. First, the integrated scheme is based on the fuzzy AHP, where the cost coefficient and the demand quantities are modeled as fuzzy numbers to measure different uncertain factors. Second, the linear programming is introduced for cost optimization to calculate the operational objective function of the reverse logistics network. Third, some experiments are made to verify the proposed model. According to different uncertain factors, the optimal cost strategy can be constructed for uncertain use demand. Last, some interesting conclusions are drawn on the proposed method for decision makers to optimize the cost of the reverse logistics network, and future work direction is also provided.

Development and evaluation of the many-to-many supplier negotiation strategy

Supply chain is a complex logistics network, consists of suppliers, manufacturers, warehouses, distribution centers, retailers and customers. In general, the number of firms in each supply chain tier is more than one. Thus, the supply–demand relationship of two adjacent tiers in supply chain is the many-to-many type. Most of supplier selection processes are based on bidding and negotiation mechanism. Due to the diversity of intellectual backgrounds of the negotiating parties, competitive nature, many variables involved in supply–demand relationship, complex interactions and inadequate negotiation knowledge of project participants, the supplier negotiation process is sophisticated. This paper intends to develop the many-to-many supplier negotiation process, design the interactive and competitive bidding strategies of both-side parties, and conduct experimental simulations to investigate how the negotiation efficiency influenced by the varying bidding strategies of a considered demander. The purpose of this paper is to explore the relationships between a demander’s bidding strategies and negotiation efficiency under different order and competitive conditions. The explorative results will be the decision support for assisting a demander to determine the proper bidding strategy in many-to-many supplier negotiation process.

IT enabled logistics procedure redesign for high value pharmaceutical shipments

PurposeThe purpose of this paper is to introduce a method for (re)designing complex logistics networks, which interact with various governmental bodies (e.g. in FDA and USDA) for regulatory clearance and control purpose. The method (the e3‐control methodology) is demonstrated to be a useful approach to analyzing and redesigning international logistics procedures in reaction to a technological innovation in a government‐business (G2B) network.Design/methodology/approachAn action research method relying on Living Lab study was used in this research. To illustrate and better understand the application of the e3‐control methodology, the authors place the development of e3‐control as a design tool for deploying the pharmaceutical case. The authors collected data with multiple methods including workshops, semi‐structured interviews and document analysis.FindingsThe e3‐control methodology has been successfully applied in this paper to carry out a step‐by‐step redesign for an international pharmaceutical logistics network. It was found that a win‐win situation can be achieved if business and government see each other as partners and share the responsibility of carrying out government regulatory and Customs controls. In this situation, Customs administrations can be relieved from redundant control tasks, and businesses will be rewarded with simplified procedures.Originality/valueThe authors' e3‐control methodology is an innovative redesign methodology for analyzing and redesigning business logistic networks including government agencies. With this approach, one can achieve a clear overview on critical problems within the logistics chains; disclose unclear procedures and in the meanwhile take into consideration the different concerns of the partners within the network.

Production planning of a hybrid manufacturing–remanufacturing system under uncertainty within a closed-loop supply chain

This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations within a closed-loop reverse logistics network with machines subject to random failures and repairs. While consumers traditionally dispose of products at the end of their life cycle, recovery of the used products may be economically more attractive than disposal, while remanufacturing of the products also pursues sustainable development goals. Three types of inventories are involved in this network. The manufactured and remanufactured items are stored in the first and second inventories. The returned products are collected in the third inventory and then remanufactured or disposed of. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the sum of the holding and backlog costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The optimality conditions are developed using the optimal control theory based on stochastic dynamic programming. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is discussed depending on the value of costs and parameters and extensions to more complex reverse logistics networks are discussed.

Proactive logistics risk management &amp;ndash; a system dynamics modelling approach

The relationships among organisations, suppliers as well as customers have resulted in complex logistics networks and have led to an increased set of risks that need to be managed in multi-site, multi-partner projects. In this article, a framework is built which incorporates both scientific and industrial feedback gathered. A system dynamics approach is utilised which simulates several risks identified in supply chain networks to establish inter and intra-relationships between various risk factors in the entire enhanced network of engineering projects. The environmental, organisational and supply chain networks related issues are considered by developing several influence diagrams for proactive logistics management.

Agent Directed HLA Simulation for Complex Supply Chain Modeling

The authors outline a new modeling methodology designed to simulate a complex logistics network and to ensure interoperability through application of Intelligent Agent High-Level Architecture for distributed supply chain management.