Regional Distribution Centers Research Articles

OPTIMIZING INVENTORY MANAGEMENT: AMAZON’S STRATEGIES IN RURAL SUPPLY CHAINS

The world's largest online retailer, Amazon, has invested heavily in infrastructure and technology to save costs and improve operations. Amazon has the most efficient supply chain in the world due to cutting-edge robotics and artificial intelligence (AI) technology that can improve productivity and worker safety. Amazon's regional distribution centers use advanced algorithms, route optimization technology, and mapping tools to effectively handle deliveries in rural areas. Artificial intelligence (AI) technologies, machine learning, and Amazon Prime membership are some initiatives that personalize recommendations and enhance the purchasing experience. To get around logistical challenges in rural locations, Amazon also collaborates with regional businesses and delivery services. To save expenses and wait times for last-mile deliveries in remote places, Amazon has made investments in micro-fulfillment centers to reduce last-mile delivery time and costs in rural areas.

A decomposition and coordination method for optimising (Q, S ) policies in a two-echelon distribution system with joint replenishment

A continuous-review, two-echelon distribution system with one central distribution centre (CDC) and multiple regional distribution centres (RDCs) is studied. The CDC jointly replenishes its inventories of multiple items from an external supplier, while each RDC replenishes its inventories of the items from the CDC. Each RDC faces a Poisson demand for each item, and the inventories of each stock in the system are controlled by a (Q, S ) policy. Under this policy, an order is placed by a stock whenever its aggregate demand since the last order reaches a given quantity, and the inventory position of each item is raised up to its order-up-to level after the order placement. The objective is to optimise these (Q, S ) policies so that the expected total cost of this system is minimised. We propose a decomposition and coordination method for this optimisation after deriving analytically the cost function of the system. Our extensive numerical experiments demonstrate the effectiveness of the proposed method. Furthermore, a parameter sensitivity analysis is conducted to analyse the impacts of some key system parameters on the performance of the method, and managerial insights are provided for optimising distribution systems with joint replenishment and real applications of the method.

The Fairness and Influencing Factors of the Spatial Distribution of Public Services in Beijing–Tianjin–Hebei

Achieving the equalization of public services is one of the main goals of regional highquality development at this stage. It plays an important guiding role in optimizing the spatial pattern of a metropolis. Taking Beijing–Tianjin–Hebei as the research area, this paper used hotspot analysis, spatial measurement, and other methods to conduct quantitative analysis and empirical research based on POI data, census data, etc., to identify regional public service centers and population distribution centers, and compared and matched them. This study built public service evaluation indicators, comprehensively evaluated the public service level of each district and county in the region, established a spatial error model, and empirically analyzed the differences in the comprehensive public service level of 200 districts and counties in the Beijing–Tianjin–Hebei region. The results show that there is a certain degree of mismatch between the comprehensive hotspots of density of public service facilities and the hotspots of permanent populations in the Beijing–Tianjin–Hebei region. The spatial differentiation of the comprehensive level of public services is obvious, showing the characteristics of “high, middle, and low in the north” and “high in the core urban area and low in other districts and counties”. Government policies, economic development level, and the level of urbanization have a significant positive effect on the public service level. The article also discussed the policy implications of the conclusions, as well as corresponding countermeasures and suggestions.

Rainfall Similarity Search Based on Deep Learning by Using Precipitation Images

Precipitation images play an important role in meteorological forecasting and flood forecasting, but how to characterize precipitation images and conduct rainfall similarity analysis is challenging and meaningful work. This paper proposes a rainfall similarity research method based on deep learning by using precipitation images. The algorithm first extracts regional precipitation, precipitation distribution, and precipitation center of the precipitation images and defines the similarity measures, respectively. Additionally, an ensemble weighting method of Normalized Discounted Cumulative Gain-Improved Particle Swarm Optimization (NDCG-IPSO) is proposed to weigh and fuse the three extracted features as the similarity measure of the precipitation image. During the experiment on similarity search for daily precipitation images in the Jialing River basin, the NDCG@10 of the search results reached 0.964, surpassing other methods. This indicates that the method proposed in this paper can better characterize the spatiotemporal characteristics of the precipitation image, thereby discovering similar rainfall processes and providing new ideas for hydrological forecasting.

Analysis on the Development Situation, Challenges and Countermeasure of Cold Chain Logistics in China

In the process of economic development and operation in China, cold chain logistics plays a huge role. Running through agriculture, industry and service sectors, cold chain logistics is an important industry for China to win the critical battle against poverty and raise consumption level, and it is also the key enterprises paid attention to by Chinese policies. Regarding the construction of dual-cycle development pattern and the further development of logistics industry, cold chain logistics plays a pivotal role and is an important basis for the construction of major route, regional distribution centers and terminal distribution nodes, so China must continuously strengthen the development of cold chain logistics to achieve further development in economy. But in current society, cold chain logistics still has many demerits. In order to reinforce relevant construction and drive economic development, this paper analyzed the development situation of cold chain logistics in China, and made a thorough analysis on the challenge to find the countermeasures to promote its development.

Allocation of products to a heterogeneous fleet of trucks in a cross-docking center based on carbon emissions and costs in food and beverage industry: Novel uncertain solution approaches

The threat of climate change continues to grow, which calls for strategies to reduce emissions. Carbon emissions from transportation are among the highest in the world, so it is essential to improve its efficiency. Cross-docking is a smart way to improve the efficiency of transportation operations through the optimal use of truck capacity. This paper develops a novel bi-objective mixed integer linear programming (MILP) model to determine which products should be shipped together, select the most appropriate truck among the available ones, and schedule them. It reveals a new class of cross-dock truck scheduling problems, in which products are not interchangeable and are sent to different destinations. The first objective is to minimize overall system costs, while the second is to minimize total carbon emissions. To deal with uncertainties in factors, such as costs, time, and emission rate, these parameters are considered interval numbers. Furthermore, innovative uncertain approaches are introduced under interval uncertainty based on optimistic and pessimistic Pareto solutions for solving MILP problems via epsilon-constraint and weighting methods. The proposed model and solution procedures are used for planning an operational day at a regional distribution center (RDC) of a real food and beverage company, and results are compared. The results show that the proposed epsilon-constraint method outperforms the other implemented methods in terms of quantity and variety of optimistic and pessimistic Pareto solutions. Using the newly developed procedure, the amount of carbon produced by trucks could decrease by 18% under optimistic assumptions and 44% under pessimistic assumptions. As a result of the proposed solution approaches, managers can observe how their optimism level and the importance of objective functions influence their decisions.

Розробка методики визначення розміру страхового запасу товарів в транспортно-логістичному ланцюзі для підвищення конкурентоздатності підприємства

The methodology of inventory management in the transport and logistics chain was developed based on the justification of organizational decisions, the characteristics of the inventory management system in the intermediate link of the logistics chain (regional transport and distribution center), which interacts with manufacturers, consumers and carriers of goods. The proposed method of determining the size of the insurance stock in the transport and logistics chain is an alternative to traditional methods that depend only on the time of late delivery due to the fault of the carrier. This allows not only to calculate the required size of the insurance stock in the system, but also to draw conclusions about the reliability of enterprises that supply and transport goods. Analysis of the necessary level reliability of the transport and logistics chain determines the quality of logistics service and allows taking into account the well-founded characteristics of the operation of the transport and logistics chain.The results of the study are proposed to be used in the process of optimizing the functioning of the enterprise in the market of goods sales.

Evaluation of land parcels for potential logistics use at regional level

Logistics activities contribute to a large part of land consumption. For various reasons, logistics is being noticeably pushed out of urban areas. The selection of the location is a decisive starting point for savings in mileage and thus CO2 savings, though.Therefore, an approach is presented here which qualifies land parcels for logistics use on regional planning level. Economic location factors, proximity-related location factors, accessibility-related location factors and the compatibility of potential logistics facilities to adjacent land uses are thereby investigated for each land parcel. This evaluation is done for five different types of logistics locations, taking into account the respective relevant location factors. The results for the regional distribution centres show that there is need for action and further research.

시스템 다이내믹스를 활용한 Covid-19 물류대란에서의 채찍현상에 관한 연구

Purpose Triggered by the measures taken to manage Covid-19, the increase in supply uncertainty and demand distortion in the market caused information asymmetry that led to the bullwhip effect of supply chain. We study the factors that affect the bullwhip effect caused by Covid-19 as well as its aftermaths. Methods We designed a stock flow diagram to analyze the bullwhip effect based on a supply chain simulation using system dynamics and also perform a causal analysis on variables affecting the supply. Results The results show that the increase in safty inventory, reduction of ship delays, and information sharing can reduce the bullwhip effect while dampening the amplification of orders in the global supply chain consisting of a retailer, a RDC (Regional Distribution Center) and a manufacturer. Conclusion A research model that analyzes the bullwhip effect of the covid-19 logistic crisis using system dynamics is proposed. The model is expected to serve as a useful tool to analyze and manage potentially uncertain global supply chain risk scenarios caused by disruptive events such as Covid-19.

Optimizing a multi-echelon location-inventory problem with joint replenishment: A Lipschitz [formula omitted]-optimal approach using Lagrangian relaxation

This paper investigates a supply network design problem for cross-border e-commerce. The supply chain consists of suppliers, regional distribution centers, and distribution centers. Our goal is to determine simultaneously location decisions of regional distribution centers, and the inventory decisions for coordinated replenishment and delivery. We formulate this problem as a mixed-integer non-linear program, and develop a Lipschitz optimization algorithm and an iterative heuristic to solve it. Moreover, we propose a tight lower bound via constructing a dual problem. Computational results show that both the Lipschitz optimization method and the heuristic can produce a near-optimal solution with a gap below 1%. Finally, we analyze the influence of integrated decision making and capacity constraints. An interesting finding is that the capacity of regional distribution centers has a critical influence, while the capacity of distribution centers is trivial. Integrated decision making can achieve remarkable cost savings only if the capacity constraints of regional distribution centers are loose. Nevertheless, capacity constraints of distribution centers make almost no impact. This result can be a good guide for a company’s investment plan: one should give top priority to regional distribution centers, and give only low priority to distribution centers.

Warehouse Automation

Abstract: This paper examines Warehouse Automations using RFID practices and their effects on operations. This study analyses the relationship between adoption of WMS to its impacts on business performance and competitive advantage of a regional distribution centre. In terms of business performance, the focus is placed on various competitive cores of distribution centre. WMS was found has a positive impact on companies' performance on operations management measures. To adopt the MIS, wireless barcode embedded WMS in specific, it is necessary to have corporate culture that supports complex operational activities. WMS implementation is crucial in bringing cost reduction in operational level, effective management in management level, as well as improvement of the company's competitiveness in strategic level. Companies that manage warehousing of their products are expected to implement WMS in order to maintain their competitive edge in the global market place.

Ripple effect mitigation capabilities of a hub and spoke distribution network: an empirical analysis of pharmaceutical supply chains in India

In this study, we focus on ripple effect mitigation capability of the Indian pharmaceutical distribution network during disruptions like COVID-19 pandemic. To study the mitigation capabilities, we conduct a multi-layer analysis (network, process, and control levels) using Bayesian network, mathematical optimisation, and discrete event simulation methodologies. This analysis revealed an associative relationship between ripple effect mitigation capabilities and network design characteristics of upstream supply chain entities. Using stochastic optimisation and Lagrangian relaxation, we then find ideal candidates for regional distribution centres at the downstream level. We then integrate these downstream locations with other supply chain entities for building the network optimisation and simulation model to analyse overall performance of the system. We demonstrate utility of our proposed methodology using a case study involving distribution of N95 masks to ‘Jan Aushadhi’ (peoples’ medicines) stores in India during COVID-19 pandemic. We find that supply chain reconfiguration improves service level to 95.7% and reduces order backlogs by 10.7%. We also find that regional distribution centres and backup supply sources provide overall flexibility and improve occupational health and safety. We further investigate alternate mitigation capabilities through fortification of suppliers’ workforce by vaccination. We offer recommendations for policymakers and managers and implications for academic research.

Инновационная технология терминальной переработки контейнеров

The article discusses a new technology of terminal processing of container traffic, which involves direct transfer of containers by rail mounted gantry cranes between groups of railcars instead of additional shunting procedures for their selection before supplying and withdrawal at loading and unloading railway tracks. In order to implement the accessibility to the gantry crane span, the additional loading and unloading railway track is introduced, intended to discard incoming containers by a gantry crane and their transhipment to the trains marshalling in the specific destination. This technology is applicable in the organization of container trains in regional distribution and storage centers and in the implementation of modal container block-trains with loading and unloading procedures in the same direction. Based on the analysis of technical development of the terminal network, the opportunity of implementing the proposed approach on Russian railways has been provided. The effect of this innovative technology is proposed to be evaluated from the perspective of decreasing the duration of rolling stock handling and, accordingly, reducing the operating costs of a terminal. The simulation of the terminal processing time of a container flow with the traditional and new approaches was carried out on the basis of the Monte Carlo method. On the basis of modeling, the dependence of the magnitude effect size on the number of the containers transhipped is determined.

A new metaheuristic approach for the meat routing problem by considering heterogeneous fleet with time windows

Guided by a real case, this paper efficiently proposes a new metaheuristic algorithm based on Simulated Annealing to solve the Heterogeneous Vehicle Routing Problem with Time Windows to deliver fresh meat in urban environments. Our proposal generates an initial feasible solution using a hybrid heuristic based on the well-known Travelling Salesman Problem (TSP) solution and, subsequently, refining it through a Simulated Annealing (SA). We have tested the efficiency of the proposed approach in a company case study related to the planning of the transportation of a regional distribution center meat company to customers within the urban and rural perimeter of Bogotá, Colombia. The main goal is to reach a service level of 97% while reducing operational costs and several routes (used vehicles). The results show that the proposed approach finds better routes than the current ones regarding costs and service level within short computing times. The proposed scheme promises to solve the refrigerated vehicle routing problem.

Managing a Hybrid RDC‐DC Inventory System

In this study, we study a hybrid RDC‐DC serial inventory system where the regional distribution center (RDC) replenishes its stock from an outside supplier (OS), while the distribution center (DC) faces random demand and replenishes its stock from the RDC. Unlike in the traditional serial system, the DC itself can replenish its inventory from outside as well. We firstly derive structural properties for the optimal long‐run average cost and the optimal stationary policy by vanishing discount approach, and then propose two simple and easy‐to‐implement policies. The first policy, which we call the three‐index policy, combines the characteristics of the echelon‐base‐stock policy for the serial system (Clark and Scarf. 1960. Management Sci.6(4): 475–490) and the dual‐index policy for the dual‐sourcing system (Veeraraghavan and Scheller‐Wolf. 2008. Oper. Res.56(4): 850–864). We show that the order‐up‐to level of the DC from the RDC can be computed by a newsboy fractile. A simulation‐based optimization procedure for the policy is provided. We then develop the approximate linear programming ( ALP) policy based on the three‐index policy and the multimodularity of the problem. This policy applies the linear programming approach to approximately solve the value function of the dynamic programming formulation. Numerical results show that both the three‐index policy and the ALP policy are comparable to the optimal policy computed via dynamic programming, and the latter performs slightly better. Moreover, the OS of the DC can draw considerable cost savings under both policies. We also conduct a numerical study with problem parameters calibrated using actual data from a consumer goods company in China to glen insights on the management of the system.

Determinants of formation of agro-food chains in the environment of households of Ukraine

The article is devoted to the study of the determinants of the formation of agri-food chains in the households of Ukraine and the substantiation of the directions of their integration into competitive supply chains. It is argued that the developments in both scientific and practical aspects of creating conditions and prerequisites for the integration of PF in the competitiveness of the supply chain and increasing value added at each level of its participants are relevant. It is highlighted that local supply chains in foreign practice are considered as tools for generating income of the rural population, the implementation of the principles of sustainable development of rural areas, as well as considered as short, local and "smart chains". It is substantiated that it is the promotion of the development of local agricultural chains with the involvement of PF in domestic practice that will contribute to the sustainable development of rural areas, ensuring food security of the country. It is argued that in order to create preconditions and conditions for the development of rural households for crop production, it is necessary to develop measures to streamline sales channels and include them in competitive supply chains. It is established that a significant part of agricultural products grown by households is used for self-sufficiency of the family, feed for farm animals and poultry, and surplus products, especially in remote rural areas, are lost due to spoilage and unclaimed. It is clear that the informal relationship between the distribution and exchange of crop products produced in PF is not a tool to maximize the profits of their members. and, therefore, it is advisable to create favorable economic conditions for their inclusion in the supply chain of agricultural production. The characteristic properties of commodity parties, PF are systematized, namely: small volumes of production, low technological standards, limited production resources, which limits the opportunities to use the potential opportunities to return capital on a scale. It was found that a certain part of the grown crop products is sold by PF through a network of retail food markets, the sale of fruits and vegetables and potatoes is carried out through retail organizations, wholesale markets for agricultural products and trade intermediaries. Measures are proposed to integrate PF into value chains on the basis of creating a network of regional wholesale and distribution centers and organizing units for purchasing surplus agricultural products, deepening the development of agricultural cooperation. Key words: agricultural sector, employment, rural households, small farmers, competitive supply chains.

A simulated annealing-based approach for a real case study of vehicle routing problem with a heterogeneous fleet and time windows

We propose a meta-heuristic algorithm for addressing a real case of vehicle routing problem with a heterogeneous fleet and time windows. Our proposal consists of generating an initial feasible solution using the solution of a travelling salesman problem and, subsequently, refining it through simulated annealing. In this work, we evaluate the suitability of our development to planning the distribution of a regional distribution centre of a food company to customers within the urban perimeter of Cali, Colombia. Following the company's customer satisfaction goals, our primary aim is to route to reach a service level of 95% while reducing operational costs. Our results on our real case study show that our meta-heuristic algorithm finds better routes than current ones, in terms of costs and service levels, in a relatively short time.

Socio-Economic Factors and their Influence in Adoption of Agricultural Technologies Under Subsistence Economy; A Case of Tissue Culture Banana in Uganda

Uptake of improved agricultural technologies like banana tissue culture still remains low despite the efforts that have been put in place to enhance its adoption. A survey was carried out on 115 smallholder farmers in central Uganda to establish the influence of various socio-economic factors on the adoption of tissue culture banana between January and July 2018. Findings from the study revealed that respondents’ main occupation (P = 0.028), market accessibility (P = 0.006) and proximity to the source of planting materials (P = 0.000) were the major drivers to adoption of tissue culture banana. The study thus recommended the establishment of regional distribution centres for tissue culture banana plantlets, increased investment in extension in order to strengthen the farmer-researcher linkage and increased market access.

Impacts of home cooking methods and appliances on the GHG emissions of food.

Food is widely acknowledged as a major contributor to climate change but estimates of food-related greenhouse gas (GHG) emissions frequently consider supply chain stages only up to the farm gate or regional distribution centres. Here we estimate GHG emissions associated with different cooking methods and appliances in the UK. Data on current cooking practices were collected through a survey with more than 700 respondents. Our results reveal that home cooking accounts for as much as 61% of total emissions associated with specific foods, and that this can be substantially reduced through alternative, readily available cooking practices.

Multi-Item Online Order Fulfillment: A Competitive Analysis

The boom of e-commerce around the globe in recent years has expedited the expansion of fulfillment infrastructures by e-retailers. While e-retailers are building more warehouses to offer faster delivery service than ever, the associated fulfillment costs have skyrocketed over the past decade. In this paper, we study the problem of minimizing fulfillment costs, in which an e-retailer must decide which warehouse(s) will fulfill each order, subject to warehouses’ inventory constraints. The e-retailer can split an order, at an additional cost, and fulfill it from different warehouses. Making effective real-time fulfillment decisions at the occurrence of order split is notoriously challenging, which has become a major problem for e-retailers. We focus on an RDC-FDC distribution network that major e-retailers have implemented in practice. In such a network, the upper layer contains larger regional distribution centers (RDCs) and the lower layer contains smaller front distribution centers (FDCs). We analyze the performance of a simple myopic policy that does not rely on demand forecasts and has been widely implemented in practice. We provide theoretical bounds on the performance ratio of the myopic policy compared with an optimal clairvoyant policy. We also empirically estimate our upper bound on the ratio by using FedEx shipping rates and demonstrate the bound can be as low as 1.13 for reasonable scenarios in practice. Moreover, we extend our study to the setting in which demand forecasting is available and prove the asymptotic optimality of a linear program rounding policy. Finally, we complement our theoretical results with a numerical study.