Showing papers on "Distribution center published in 2017"

Product variety, sourcing complexity, and the bottleneck of coordination

Abstract: Research summary: This paper studies the coordination burden for firms that pursue variety as their main product strategy. We propose that product variety magnifies the tension between scale economies in production and scope economies in distribution, giving rise to complex sourcing relationships. Sourcing complexity worsens performance and poses a dilemma for organization design: A hierarchical structure with intermediate coordinating units such as sourcing hubs reduces sourcing complexity for downstream distribution but creates bottlenecks at the hubs, hurting performance for both the hubs and downstream distribution. We empirically examine operations data for about 300 distribution centers within a major soft drink bottling company in 2010–2011. Results support our hypotheses, illuminating the source of complexity in multi-product firms and the challenge for organization design in managing complexity. Managerial summary: This paper uses data for about 300 distribution centers within a major soft drink bottling company to study how a large product variety creates complex sourcing networks. We find that, in addition to poor performance (e.g., increased stockouts), complex sourcing networks can cause challenges for organization design. In particular, the benefits of converting an existing distribution center into a sourcing hub (i.e., reduction in sourcing complexity for downstream distribution) and the costs of doing so (i.e., reduction in performance for both the hubs and downstream distribution) are both real and significant. The design of an efficient sourcing network despite its complexity involves important managerial decisions. Experiences in building and managing such networks can be the basis of a dynamic capability. © 2016 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.

Optimal Wave Release Times for Order Fulfillment Systems with Deadlines

Abstract: Service performance of an order fulfillment system is mainly determined by how quickly and accurately it fills customer orders. A higher service level can be offered with a later cutoff time, before which customers are assured of receiving their orders. However, the desire to offer a later cutoff time must be tempered by the need to provide service at low cost, which means taking advantage of economies of scale in picking operations. To strike this balance, many distribution centers release orders in large batches called waves. We develop analytical models to determine the timing and the number of order waves for fulfillment systems that operate against a daily deadline. In a case study, we apply our theoretical models to data from a large distribution center and show that optimal wave releases could significantly improve on time shipments compared to an intuitive method.

Location Selection of Logistics Center in e-Commerce Network Environments

Abstract: The site selection of logistics center is a very complicated and enormous system problem. Each site selection method and model is based on a certain premise and hypothesis. The site selection decision of distribution center has an important influence on the whole logistics system operation. A good location of urban logistics sites is important for optimizing the logistics network, and improving the urban traffic conditions, and level of logistics services. Motivated by this, in this paper, based on the research of sixteen cities in southeastern China and neural network algorithms, we proposed a logistics center location selection algorithm. Our method considers the six important concepts reflecting the performance index of the city logistics, such as city location quotient, market prosperity degree, proportion of freight volume, urban centricity, per capita gross domestic product (GDP), and population size. Our method conducts the nested fuzzy analytic hierarchy process (AHP), and then investigates the total ranking of the single order hierarchy to select suitable logistics centers.

Storage allocation framework for designing lean buffers in forward-reserve model: a test case

Abstract: Purpose The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers. Design/methodology/approach After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization. Findings The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area. Originality/value The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations.

Prioritizing high-risk sub-groups in a multi-manufacturer vaccine distribution program

Abstract: Purpose Annual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza vaccination program (VP). The goal is to minimize the total cost of the vaccination supply chain while guaranteeing a sufficiently high level of population protection. From a practical point of view, the analysis returns the number of shipments and the quantity of vaccines in each periodic shipment that should be delivered from the manufacturers to the distribution center (DC), from the DC to the clinics, and from the clinics to each sub-group of customers during the vaccination season. Design/methodology/approach A mixed-integer programming optimization model is developed to describe the problem for a supply chain consisting of vaccine manufacturers, the healthcare organization (HCO) (comprising the DC and clinics), and the population being vaccinated (customers). The model suggests a VP that implemented by a nation-wide HCO. Findings The benefits of the proposed approach are shown to be particularly salient in cases of limited resources, as the model distributes demand backlogs in an efficient manner, prioritizing high-risk sub-groups of the population over lower-risk sub-groups. In particular, the authors show a reduction in direct medical burden of consumers, such as the need for doctors, hospitalization resources, and reduction of indirect, non-medical burden, such as loss of workdays. Practical implications Drawing from the extended enterprise paradigm, and, in particular, taking consumer benefits into account, the authors suggest an operational-strategic model that creates impressive added value in a highly constrained supply chain. The model constitutes a powerful decision tool for the deployment of large-scale seasonal products, and its implementation can yield multiple benefits for various consumer segments. Originality/value The model proposed herein constitutes a decision support tool comprising operational-tactical and tactical-strategic perspectives, which logistics managers can utilize to create an enterprise-oriented plan that takes into account medical and non-medical costs.

Automated retail supply chain and inventory management system

Abstract: A system and method are disclosed for supplying one or more goods to a physical store location. The goods may be received at a distribution center (DC). At the DC, the goods may be decanted from their shipping containers into one or more sub-totes, which are contained within one or more product totes. The sub-totes may be transferred from the one or more product totes to one or more order totes based on a velocity of movement of the plurality of goods at the physical store location.

Solving an emergency rescue materials problem under the joint reserves mode of government and framework agreement suppliers.

Abstract: Emergency rescue material reserves are vital for the success of emergency rescue activities. In this study, we consider a situation where a government owned distribution center and framework agreement suppliers jointly store emergency rescue materials. Using a scenario-based approach to represent demand uncertainty, we propose a comprehensive transportation pattern for the following supply chain: "suppliers-government distribution center-disaster area." Using a joint reserves model that includes the government and framework agreement suppliers, we develop a non-linear mathematic model that determines the choices of the framework suppliers, the corresponding optimal commitment quantities, and the quantity of materials that are stored at a government distribution center. Finally, we use IBM ILOG CPLEX to solve the numerical examples to verify the effectiveness of the mode and perform sensitivity analyses on the relevant parameters.

Green facility location

Abstract: Transportation is one of the main contributing factors of global carbon emissions, and thus, when dealing with facility location models in a distribution context, transportation emissions may be substantially higher than the emissions due to production or storage. Because facility location models define the configuration of deliveries, green location models become an important alternative to reduce CO2 emissions in logistics.

Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load

Abstract: Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL) are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting Genetic Algorithm II (NSGA-II) is designed to obtain candidate transport paths. Second, with analysis on the operating process of vehicles with hazardous materials in FCL, the vehicle scheduling problem is converted to Vehicle Routing Problem with Time Windows (VRPTW). A problem-solving method based on estimation of distribution is adopted. A transport timetable for all vehicles based on their transport paths is calculated, with participation of the decision-makers. A visual vehicle scheduling plan is presented for the decision-makers. Last, two examples are used to test the method proposed in this study: distribution of hazardous materials in a small-scale test network and distribution of oil products for sixteen gas stations in the main districts of Lanzhou city. In both examples, our method is used to obtain the path selection and vehicle scheduling plan, proving that validity of our method is verified.

Multisourcing supply network design : two-stage chance-constrained model, tractable approximations, and computational results

Abstract: In this paper, we study a multisourcing supply network design problem, in which each retailer faces uncertain demand and can source products from more than one distribution center (DC). The decisions to be simultaneously optimized include DC locations and inventory levels, which set of DCs serves each retailer, and the amount of shipments from DCs to retailers. We propose a nonlinear mixed integer programming model with a joint chance constraint describing a certain service level. Two approaches—set-wise approximation and linear decision rule-based approximation—are constructed to robustly approximate the service level chance constraint with incomplete demand information. Both approaches yield sparse multisourcing distribution networks that effectively match uncertain demand using on-hand inventory, and hence successfully reach a high service level. We show through extensive numerical experiments that our approaches outperform other commonly adopted approximations of the chance constraint.

A Collection-Distribution Center Location and Allocation Optimization Model in Closed-Loop Supply Chain for Chinese Beer Industry

Abstract: Recycling waste products is an environmental-friendly activity that can result in manufacturing cost saving and economic efficiency improving. In the beer industry, recycling bottles can reduce manufacturing cost and the industry’s carbon footprint. This paper presents a model for a collection-distribution center location and allocation problem in a closed-loop supply chain for the beer industry under a fuzzy random environment, in which the objectives are to minimize total costs and transportation pollution. Both random and fuzzy uncertainties, for which return rate and disposal rate are considered fuzzy random variables, are jointly handled in this paper to ensure a more practical problem solution. A heuristic algorithm based on priority-based global-local-neighbor particle swarm optimization (pb-glnPSO) is applied to ensure reliable solutions for this NP-hard problem. A beer company case study is given to illustrate the application of the proposed model and to demonstrate the priority-based global-local-neighbor particle swarm optimization.

Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Abstract: The problem of locating distribution centers for delivering fresh food as a part of electronic commerce is a strategic decision problem for enterprises. This paper establishes a model for locating distribution centers that considers the uncertainty of customer demands for fresh goods in terms of time-sensitiveness and freshness. Based on the methodology of robust optimization in dealing with uncertain problems, this paper optimizes the location model in discrete demand probabilistic scenarios. In this paper, an improved fruit fly optimization algorithm is proposed to solve the distribution center location problem. An example is given to show that the proposed model and algorithm are robust and can effectively handle the complications caused by uncertain demand. The model proposed in this paper proves valuable both theoretically and practically in the selection of locations of distribution centers.

Adaptive Levy distribution hybrid mutation improved artificial fish swarm algorithm-based distribution center site selection optimization method

Abstract: The invention belongs to the logistics distribution site selection technical field and relates to an adaptive Levy distribution hybrid mutation improved artificial fish swarm algorithm-based distribution center site selection optimization method. The method includes the following steps that: (1) relevant parameters are initialized, and a distribution center site selection optimization model is established; (2) the distribution center site selection optimization model is solved through using the optimization method according to which adaptive Levy distribution hybrid mutation is utilized to improve an artificial fish swarm algorithm; and (3) a distribution center site selection result is compared with the result of using the adaptive Levy distribution hybrid mutation to improve the artificial fish swarm algorithm in solving a distribution center site selection problem. According to the method of the invention, Levy mutation and chaotic mutation are introduced into the basic fish swarm algorithm, so that the diversity of artificial fish states in the basic artificial fish swarm algorithm can be increased, the capability of the basic artificial fish swarm algorithm to jump out of local optimum can be improved, and the optimization of distribution center site selection can be enhanced.

Logistics distribution planning method, logistics distribution method, and device thereof

Abstract: The invention provides a logistics distribution planning method, a logistics distribution method, and a device thereof. The logistics distribution planning method comprises steps that a distribution time efficiency tree is generated according to a state of a road network constituted by various distribution nodes, and the distribution nodes comprise a distribution center and one or a plurality of distribution stations, and the distribution center is used for management of distribution vehicles; according to the cargo quantities of the various distribution stations and data related to the vehicles of the distribution center, a distribution route is planned by using the distribution time efficiency tree; according to the distribution route, a distribution vehicle scheduling scheme is generated. Logistics distribution planning is realized in a high-efficiency way.

Agricultural product co-production and distribution and group exhibition and joint-sale e-commerce platform

Abstract: The present invention discloses an agricultural product co-production and distribution and group exhibition and joint-sale e-commerce platform. The platform constructs an e-commerce operation and management system of linkage joint sale between agricultural product production bases and city direct-sale stores and group exhibition and joint-sale of different farm villages and stores of distinctive agricultural products at different areas on a national scale. An operation platform collects purchase orders of different stores in an area to form purchase orders at scale to directly join with the product enterprises for ordering, the bases are responsible for distributing the products to each area distribution center to complete the whole process of the agricultural product transaction so as to shorten the agricultural product transaction intermediate link. Offline farm sites display images and objects of distinctive agricultural products across the country, the product details are understood through scanning two-dimensional codes, and ordering and transaction can be performed in the e-commerce platform so as to realize group exhibition and joint-sale. The dual-brand mechanism of platform+enterprise brand of agricultural products in the city stores are realized so as to realize real-time live of the product production bases, enhance the user experience and improve the merchant profit level on the co-production and joint-sale ecological chain of the agricultural products by means of the internet of things.

Distribution Center capacity analysis in stochastic environment: An application of value stream analysis and Monte Carlo simulation

Abstract: The main objective of this research is to develop a simulation based capacity analysis model We applied value stream analysis and Monte Carlo simulation, in a stochastic Distribution Center (DC) operations environment, in order to analyze the capacity level and make informed staffing and operations decisions A simulation model was developed to provide a baseline for management to understand workflow and DC available capacity The results showed that the DC under study was capable of receiving and shipping 30% to 40% higher units per shift In addition, the results showed that there was an imbalanced workflow caused by original flow design, and daily work scheduling and planning

Apparatus and method for providing delivery service

Abstract: An apparatus for providing a delivery service according to an embodiment of the present invention includes: a communication interface for receiving order information from a buyer terminal; a database for storing information related to a distribution center; and a processor for extracting the distribution center capable of providing a product according to the order information, determining the priority of the plurality of centers by using the information related to the distribution center when a plurality of distribution centers are extracted, and selecting the distribution center of the highest ranking. Accordingly, the present invention can select the distribution center according to the purpose of delivery.

Case Article-Growing Pains: A Case Study for Large-Scale Vehicle Routing

Abstract: This is a case study focused on the quantitative modeling of transportation services for use in undergraduate and graduate level transportation and logistics or optimization courses. The problem considered in the case is a capacitated vehicle routing problem CVRP with additional side constraints corresponding to delivery windows and United States Department of Transportation drive and duty time regulations. The case is presented in the context of a fictional company, Northeastern Home Goods NHG, but is based on a problem encountered by a real organization. NHG is considering outsourcing its transportation services to a firm having logistics as a core competency. Specifically, NHG wishes to evaluate the transportation costs that will result if a single distribution center is used to serve all of NHG's current stores according to a preexisting store delivery schedule. The primary objective of the case is to provide students with hands-on experience developing and applying solution techniques for a large unstructured vehicle routing problem. Secondary objectives include requiring students to think logically through the process of creating good solutions, promoting continuous improvement, and encouraging students to consider the business implications of their recommendations.

Potential of Smart Glasses in a Spare Parts Distribution Center

Abstract: The distribution of products is for many manufacturing firms a necessary yet demanding and labor intensive procedure. To fulfill the role of distribution successfully, the ability to exchange information and provide workers with information plays an important part. New technologies are developed to enable better communication of information. One emerging technology is augmented reality used with smart glasses. Smart glasses aim to visually enhance reality with additional information. Therefore, it is of interest to examine how smart glasses can be used in a distribution context. The purpose of the thesis was to identify and assess the potential of using smart glasses in Volvo Logistic Services’ distribution centers processes, compared to currently used methods. To be able to achieve the purpose, a theoretical framework was developed. In addition, the distribution center processes were mapped and further data was collected through three interviews with Volvo employees, a time study and historical performance data. The distribution center performance measures used in the thesis are productivity, quality, flexibility and ergonomics. Regarding the smart glass effect on these measures, a correlation between smart glasses and flexibility was not found. Moreover, it is concluded that smart glasses perform equally or better than current methods in regards to the performance measures. From a qualitative analysis, it is concluded that the main potential lies in using smart glasses to display additional information which today only exist through the experience of operators. Based on that statement, the potential of providing experience based information in the current distribution center processes is analyzed. Additionally, several employee suggestions of changing the processes through adding additional information is analyzed. Ultimately, two potentials were illustrated and quantified through saving estimations. In conclusion, it is recognized that the technology is rapidly developing and that smart glasses hold large potential in the future. However, it may not be sufficient to motivate a full-scale implementation of the technology in a distribution center. Instead Volvo Logistics Services are suggested to do further investigations and a proof of concept.

An Improved Distribution Policy with a Maintenance Aspect for an Urban Logistic Problem

Abstract: In this paper, we present an improved distribution plan supporting an urban distribution center (UDC) to solve the last mile problem of urban freight. This is motivated by the need of UDCs to satisfy daily demand in time under a high service level in allocated urban areas. Moreover, these demands could not be satisfied in individual cases because the delivery rate can be less than daily demand and/or affected by random failure or maintenance actions of vehicles. The scope of our work is to focus on a UDC, which needs to satisfy demands in a finite horizon. To that end, we consider a distribution policy on two sequential plans, a distribution plan correlated to a maintenance plan using a subcontracting strategy with several potential urban distribution centers (UDCs) and performing preventive maintenance to ensure deliveries for their allocated urban area. The choice of subcontractor will depend on distance, environmental and availability criteria. In doing so, we define a mathematical model for searching the best distribution and maintenance plans using a subcontracting strategy. Moreover, we consider delay for the next periods with an expensive penalty. Finally, we present a numerical example illustrating the benefits of our approach.