Showing papers on "Distribution center published in 2008"

Vehicle routing with dynamic travel times: A queueing approach

Abstract: Transportation is an important component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routes is a crucial management problem. In this paper, a vehicle routing problem with dynamic travel times due to potential traffic congestion is considered. The approach developed introduces mainly the traffic congestion component based on queueing theory. This is an innovative modeling scheme to capture travel times. The queueing approach is compared with other approaches and its potential benefits are described and quantified. Moreover, the optimization of the starting times of a route at the distribution center is evaluated. Finally, the trade-off between solution quality and calculation time is discussed. Numerous test instances are used, both to illustrate the appropriateness of the approach as well as to show that time-independent solutions are often unrealistic within a congested traffic environment, which is usually the case on European road networks.

Selecting Between Batch and Zone Order Picking Strategies in a Distribution Center

Abstract: An order picking strategy in a distribution center (DC) defines the manner in which pickers navigate the picking area to pick items from storage locations. We focus on the problem of selecting between a batch picking and a zone picking strategy. For this problem, we propose a cost model to estimate the cost of each type of picking strategy. In our cost model we consider the effects of pick-rate, picker blocking, workload-imbalance, and the sorting system requirement. Through an example problem, we show how system throughput, order sizes, item distribution in orders, and wavelength affect the picking strategy selection decision.

Allocating space in a forward pick area of a distribution center for small parts

Abstract: The forward pick area of a distribution center is a cache of conveniently located products from which order pickers can quickly draw, but which must be replenished from bulk or reserve storage. The quantities stored forward determine the amount of work required to sustain the forward pick area. Two stocking strategies that are commonly used in industry are analyzed and compared with the optimal stocking strategy for small parts.

Planning Approximations to the Average Length of Vehicle Routing Problems with Varying Customer Demands and Routing Constraints

Abstract: This paper studies approximations to the average length of vehicle routing problems (VRPs). The approximations are valuable for strategic and planning analysis of transportation and logistics problems. The focus is on VRPs with varying numbers of customers, demands, and locations. This modeling environment can be used in transport and logistics models that deal with a distribution center serving an area with daily variations in demand. The routes are calculated daily on the basis of what freight is available. New approximations and experimental settings are introduced. Average distance traveled is estimated as a function of the number of customers served and the number of routes needed. Approximations are tested in instances with different customer spatial distributions, demand levels, numbers of customers, and time windows. Regression results indicate that the proposed approximations can reasonably predict the average length of VRPs in randomly generated problems and real urban networks.

Innovations in City Logistics

Abstract: Preface Modelling the behavior of stakeholders in city logistics City access restrictions and the implications for goods deliveries City logistics over the years -- Lessons learned, research directions and interests An investigation into the attitudinal factors determining participation in cooperative multi-carrier delivery initiatives Economy of scale and the role of publicly available congestion information for the local delivery industry: an agent-based simulation approach The potential use of urban consolidation centres in the hotel industry in London Revival of cost benefit analysis for evaluating the city distribution center concept? 8 Sustainable goods supply and transport in conurbations: Freight patterns and developments in Switzerland Challenging the traditional scope of solving vehicle routing and scheduling A hybrid genetic algorithm for VRPSTW using column generation Provision of real-time traffic information for VRPTW model A macroscopic traffic simulator for evaluating urban transport measures for heavy vehicles Urban freight policy-oriented modelling in Europe Melbourne freight movement model Modeling logistics location choice and truck route choice behavior by Tokyo metropolitan region freight survey A hybrid microsimulation model of freight flows An investigation into the delivery of goods to the city centre of Liege Typology of efforts by Japanese companies to address logistics-related environmental issues Policy making in Germany -- Integrated commercial traffic concept of Berlin An evaluation of recent pick-up point experiments in European cities: The rise of two competing models? Reserved areas for logistics activities in the metropolitan zone of Mexico city Customized policies for sustainable urban distribution Metropolitan freight distribution by railways A practical approach to solving the just in time periodic transportation problem Quantifying the effects of community level regulation on city logistics Urban freight transport and logistics: Retailers choices Studying distribution in Tokyo metropolitan region using a local freight survey An analysis on bottlenecks for domestic vehicular transportation of international maritime container cargos in Japanese hinterland Citylog(c), a software tool for city logistics operation: Testing and validation activities Supply-chain logistics for retailing, from the standpoint of resource productivity: Researching a comprehensive evaluation method Light freight transport in urban areas Elements for a master plan in urban logistics New trends on distribution in the metropolitan zone of Mexico city A centre for eco-friendly city freight distribution: Urban logistics innovation in a mid-size historical city in Italy The conditions of modal shift in dense urban areas A case study of urban freight in Mexico A probabilistic bi-level optimization approach to highway infrastructure maintenance in urban areas Index.

Analysis and Optimal Design of Discrete Order Picking Technologies Along a Line

Abstract: Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e-commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology—conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design—where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single-depot, dual-depot, and no-depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 00: 000-000, 2008

Distribution center location for green supply chain

Abstract: In this paper, a simple mix integer programming for distribution center location is proposed. Based on this simple model, we introduce two important factors, transport mode and carbon emission, and extend it a model to describe the location problem for green supply chain. Sequently, IBM Watson implosion technologh (WIT) tool was introduced to describe them and solve them. By changing the price of crude oil, we illustrate the its impact on distribution center locations and transportation mode option for green supply chain. From the cases studies, we have known that, as the crude oil price increasing, the profits of the whole supply chain will decrease, carbon emission will also decrease to some degree, while the number of opened distribution center will increase.

Transshipment Problems in Supply ChainSystems: Review and Extensions

Abstract: Effective supply chain management (SCM) is currently recognized as a key determinant of competitiveness and success for most manufacturing and retailing organizations, because the implementation of supply chain management has significant impact on cost, service level, and quality. Numerous strategies for archiving these targets have been proposed and investigated in both practice and academic over the past decades. One such strategy, commonly practiced in multi-location supply chain systems facing stochastic demand, allows movement of stock between locations at the same echelon level or even across different levels. These stock movements are termed lateral transshipments, or simply, transshipments. As a demand occurs under the implementation of transshipment strategy, there will be three possible activities—the demand is met from the stock on-hand or it is met via transshipment from another location in the system or it is backordered. In another words, firstly, if a location’s on-hand inventory level is greater than the demand size, then the demand is met. Secondly, if the on-hand inventory level is positive but less than the demand size, then it is used to partially satisfy the demand and the remaining demand is met either via transshipment or is backordered. Thirdly, if the on-hand inventory level is zero, the demand is met via transshipment or is backordered under the assumption of no lost sale. In addition to the same echelon level transshipment, when neither one location’s same level partners in the same region nor its designated supplier/warehouse/or distribution center lack sufficient inventory to meet the demand, the unmet remaining demand can be fulfilled from the upper-level supplier which may not belong to the same geographical region. This practice is defined as cross-level transshipment. The illustration of transshipment is depicted in Figure 1. Therefore, transshipment policy can improve stock availability, i.e., customer service level, without increasing stock level which may induce higher inventory relevant cost. In another words, transshipments enable the sharing of stock among locations, they facilitate each location as a secondary, random supply source for the remainder. Thus, the locations’ replenishment can be coordinated and even combined in order to avoid excessive inventory costs. Transshipment research is motivated by observations from various industries. It has gained increasingly attention in medicine, apparel, and fashion goods, particularly by those retailers with brick and click outlets, or critical repairable spare parts of equipment-intensive

Optimal decision-making on product ranking for crossdocking/warehousing operations

Abstract: The physical distribution of goods is one of the key success factors in todaypsilas fast moving markets. Many companies are involved in the search for efficient distribution alternatives, as the lead times for customer order fulfillment need to be shortened while the costs and risks of warehousing need to be minimized. Crossdocking is defined as an operation strategy that moves items through flow consolidation centers or cross docks without putting them into storage. This removes the need for distribution warehouses in the supply chain, and allows the customers to receive complete deliveries for their orders. However, not all products are suitable for crossdocking operations. In real practice, a pure crossdocking scenario is not common. A crossdocking center or distribution center is normally a combination of crossdocking and warehousing facilities. Industry needs guideline and model to support crossdocking/warehousing decision-making and to evaluate the applicability of crossdocking operations for their particular business situation. This paper presents a systematic procedure and model for the evaluation of the ranking of productpsilas suitability for crossdocking in a distribution center or crossdocking center. A prototype system based on the approach had been developed and is also introduced in the paper.

Genetic algorithm solution for multi-period two-echelon integrated competitive/uncompetitive facility location problem

Abstract: This paper addresses the multi-period two-echelon integrated competitive/uncompetitive facility location problem in a distribution system design that involves locating regional distribution centers (RDCs) and stores, and determining the best strategy for distributing the commodities from a central distribution center (CDC) to RDCs and from RDCs to stores. The goal is to determine the optimal numbers, locations and capacities of RDCs and stores so as to maximize the total profit of the distribution system. Unlike most of past research, our study allows for dynamic planning horizon, distribution of commodities, configuration of two-echelon facilities, availability of capital for investment, external market competition, customer choice behavior and storage limitation. This problem is formulated as a bi-level programming model and a mutually consistent programming mode, respectively. Since such a distribution system design problem belongs to a class of NP-hard problem, a genetic algorithm-based heuristic (GA) is presented and compared with random search solution and mutually consistent solution (MC) using numerical example. The computational results show that the GA approach is efficient and the values of the performance index were significantly improved relative to the MC.

Navigation apparatus and information distribution system

Abstract: A CPU 41 of a navigation apparatus 2 stores each of public keys PK1 through PK5 to which priorities are set and which are published by an information distribution center 3 in a public key storage section 39. The CPU 41 of the navigation apparatus 2 extracts an electronic signature of distribution data which is distributed from the information distribution center 3 and verifies the electronic signature by using only 'valid' public keys among the public keys PK1 through PK5 in order of the priorities. The CPU 41 of the navigation apparatus 2 determines that the distribution data is valid information which is distributed from the information distribution center 3 when the electronic signature passes verification.

Optimal product allocation for crossdocking and warehousing operations in FMCG supply chain

Abstract: Many companies search for efficient distribution alternatives, as the lead times for customer order-fulfillment need to be shortened while the costs and risks of warehousing need to be minimized. Crossdocking is an operation strategy that moves items through flow consolidation centers or cross docks without putting them into storage. A distribution center normally is a combination of crossdocking and warehousing facilities. The operator of the center needs to be clear on what products or even how many percent of a type of product should go through by crossdocking. Industry needs guideline and model to support crossdocking/warehousing decision-making and produce alternative plan for allocating products to crossdocking and warehousing operations. This paper presents a systematic procedure and model for evaluating crossdocking distribution in a company. A prototype system based on the approach is discussed and testing analysis is given in the paper.

Design, Management and Control of Logistic Distribution Systems

Abstract: Nowadays global and extended markets have to process and manage increasingly differentiated products, with shorter life cycles, low volumes and reducing customer delivery times. Moreover several managers frequently have to find effective answers to one of the following very critical questions: in which kind of facility plant and in which country is it most profitable to manufacture and/or to store a specific mix of products? What transportation modes best serve customer points of demand, which can be located worldwide? Which is the best storage capacity of a warehousing system or a distribution center (DC)? Which is the most suitable safety stock level for each item of a company’s product mix? Consequently logistics is assuming more and more importance and influence in strategic and operational decisions of managers of modern companies operating worldwide. The Council of Logistics Management defines logistics as “the part of supply chain process that plans, implements and controls the efficient, effective flow and storage of goods, services, and related information from the point of origin to the point of consumption in order to meet customers’ requirements”. Supply Chain Management (SCM) can be defined as “the integration of key business processes from end-user through original suppliers, that provides product, service, and information that add value for customers and other stakeholders” (Lambert et al., 1998). In accordance with these definitions and with the previously introduced variable and critical operating context, Figure 1 illustrates a significant conceptual framework of SCM proposed by Cooper et al. (1997) and discussed by Lambert et al. (1998). Supply chain business processes are integrated with functional entities and management components that are common elements across all supply chains (SCs) and determine how they are managed and structured. Not only back-end and its traditional

e-based inter-enterprise supply chain Kanban for demand and order fulfilment management

Abstract: The philosophy of Kanban is that parts and materials should be supplied at the very moment they are needed in the factory manufacturing process. e-based inter-enterprise supply chain Kanban are investigated on the distribution center of a global supply chain network, with information technology based pull systems being examined from the distributors back to the suppliers. Using the qualitative case study method, the study is data from a Japan based electronics manufacturing company, regional headquarter and its distributors. The research methodology comprised of establishing the value stream mapping (VSM) supply chain network for a company and tracing this from customer order back to the manufacturing order. The research findings demonstrate the novel utility of using information technology to perform the Kanban function through the demand and order fulfilment process, from distributor back to company global headquarter. This can be achieved through the use of the Internet as the distributor and global headquarter portal for contact.

Research on Location Selection of Distribution Center

Abstract: The location selection of distribution center plays an important position in the whole logistics systemThe quantity and distribution of logistics nodes will directly affect the service cost and the range of this logistics systemThe establishment of logistics distribution center and each distribution process were studiedEach subitem of total expenditure was weighted by using entropy methodThe weight was confirmed according to the information amount provided by the actual data of each index,which reflected the importance of each item of expenditure costSo the linear expense model for the location selection was set up to make the decision more reasonablyAt last,enumeration method was used to carry on the example solution

A hybrid tabu-sa algorithm for location-inventory model with considering capacity levels and uncertain demands

Abstract: In this paper, we present a complex distribution network design problem in supply chain system which includes location and inventory decisions. Customers' demand is generated randomly and each distribution center maintains a certain amount of safety stock in order to achieve a certain service level for the customers it services. Unlike most of past research, our model allows for multiple levels of capacities available to the distribution centers. This consideration helps to achieve the capacity utilization to a high level as our computational results show this fact. We show that this problem can be formulated as a non-linear integer programming model. A hybrid heuristic combining Tabu search with Simulated Annealing (SA) sharing the same tabu list is developed for solving the problem. We comprise the hybrid algorithm with the optimal solution, Simulated Annealing algorithm and Tabu search algorithm. The results indicate that the method is efficient for a wide variety of problem sizes.

Slotting the Complex Automated Picking System in tobacco distribution center

Abstract: Tobacco distribution has the main features of fast-moving, high value, uniform dimension which requires high picking efficiency, accuracy and low labor intensity. In this case, traditional manual picking needs to be replaced by proper automated picking significantly. Complex Automated Picking System (CAPS) is a kind of automated order picking system, composed of the Horizontal Dispenser (HD) and A-frame to achieve the advantages of both. As the main order fulfillment area in tobacco distribution center, CAPS needs to be slotted significantly. Based on the classical forward-reserve model, multi-tier model and multi-mode model, we first present a comprehensive analysis of the general multi-tier, multi-mode inventory system of CAPS and analyze the restocking and picking activities of HD and A-frame. Considering the safety stock, we present the optimal number of channels assigned to each sku to minimize the restocking cost of Horizontal Dispenser (HD) based on fluid model and extend the results to A-frame. Rigorous proofs are presented for main theorems and corollaries. Then we develop a three-tier, four-mode inventory system and use it to identify the optimal proportion of picking buffer dedicated to HD and A-frame. Finally, we analyze the equivalent two-tier, three-mode inventory system and develop a practical Greedy Heuristic Strategy to slot the CAPS, which is of great significance for designing a new and measuring an already running CAPS in the tobacco distribution center.

Supply Chain Planning Processes for Two Major Retailers

Abstract: This chapter describes supply chain practices and processes observed at two retailers in the home furnishing sector. Because of the large number of stock-keeping-units (SKUs), the inter-relationships among the SKUs, as well as use of multiple store formats and multiple marketing channels targeted to different customer segments, home furnishings is one of the most complex retail sectors. In addition to documenting the complex flows of materials and information in such multi-channel environments, we present details of key supply chain planning processes: product design and assortment planning, sourcing and vendor selection, logistics planning, distribution planning and inventory management, clearance and markdown optimization, and cross-channel optimization.

Biological Clustering Method for Logistic Place Decision Making

Abstract: One of the main tasks in supply chain network is to identify the determination of logistic location. The main factors could influence the selections are costs and profits for the company itself. Most appropriate place is urgently essentials in today business world to ensure the company could be more competitive then other competitors in the industry. A lot of considerations should be taken during selecting a location to build a logistic place to serve other retailers city effectively. Currently, there are so many algorithms based on different approaches are proposed by other researchers. Thus, this paper intends to propose DNA computing approach to solve the problem. In this study, a cluster-based approach is employ when all cities are grouped before we choose a right city as distribution center. A case study is presented at the end of this paper to illustrate how the proposed technique works.

A study of multi-echelon inventory systems with stochastic capacity and intermediate product demand

Abstract: The placement of inventory with multi-echelon supply chains is a major driver of cost and level of customer service. This research studies several multi-echelon inventory systems with stochastic capacity and intermediate product demand. Specifically we analyze the behavior of a system which includes several intermediate product demands. This analysis i) develops inventory update relationships for each multi-echelon inventory system considered under several inventory allocation policies, ii) develops two simulation optimization approaches to minimize the total inventory holding cost required to meet all demands at the desired customer service level, iii) obtains results for a large number of multi-echelon inventory systems under several scenarios and instances, including an extensive analysis and implications of the results. This work is different than earlier research in the multi-echelon inventory area, since it considers a complex (combination of serial and assembly systems) multi-period, multi-echelon, inventory system with several sources of demand (specifically intermediate product demands). We obtain the optimal base-stock level for each node in the system that satisfies the required customer service level. A SIO (Simulation based Inventory Optimization) approach is used to obtain the optimal base-stock level for the system under several inventory allocation policies. We consider a system which is closer to realworld supply networks and the procedures can be used in contemporary environments like, 1) a manufacturing firm that produces finished products as well as spare parts, 2) a manufacturer – warehouse – distribution center – retail outlets network. The optimal base-stock level for each node is obtained under realistic conditions like stochastic demand, stochastic capacity, and lead time. This research utilizes two frameworks to carry out the simulation-based optimization of the inventory parameters in the mathematical model: 1) an OptQuest framework, and 2) an Infinitesimal Perturbation Analysis (IPA) framework. The primary goal is to determine optimal base stock levels for the components, intermediate product and final product based on a required customer service level at each stage. Supplier Depot 1 Retailer 1

Simulation study of miniload-workstation order picking system

Abstract: This report provides a detailed elaboration on the simulation study of a miniload-workstation order picking system, which was carried out by the Systems Engineering Group at TU/e under the FALCON project. The study is regarded as a starting point towards creating a fast, simple and accurate model for performance analysis based on simulation models. The purpose of this simulation study is to create a detailed simulation model that represents an operating, industrial scale distribution center (DC). As a reference case, an existing DC was selected. The main characteristic of the reference case DC is the use of state-of-the-art Automated Storage/Retrieval System (AS/RS), which is becoming a common practice for large scale DC. The type of AS/RS used in this DC is referred to as the miniload-workstation order picking system, or the end-of-aisle system. Our approach is to create a flexible and modular model architecture such that the model is not restricted to be used only for the reference case. The proposed architecture allows different system structures to be modeled by adding slight changes to the current architecture. The simulation model is built using a process algebra based simulation language $\chi$. The proposed model is structured into three areas and four layers. Furthermore, clustered subsystems and decentralized controls are applied to the model architecture. We validated the proposed model and performed some experiments to evaluate the performance of the DC in terms of flowtime and throughput. Furthermore, we show that different system configurations can be modeled using the proposed architecture. We conclude that our model has covered sufficient details from the reference case and hence can be used further as the base model for evaluating the performance of aggregation methods under development.

Spatial Organizational Network of Loigsitcs Company in China

Abstract: With the development of the third party logistics, logsitcs company as a professional economic form to organize logistics activities with the spatial network is well aware of the growing importance. Much attention is paid to the spatial network of logistics company. Based on discussion about research process of logistics company, this paper analyzes the theory about spatial network of logistics company and discusses its spatial system, function ties and operation mechanism. Logistics company is composed of corporation factors and logistics factors with different spatial attributions, moving regularity and organization characteristics whose united operation generates function differentiation and location separation among different members of logistics company, which develops into the spatial network including organizing network of corporation factor and operating network of logistics activities, namely the static phase and dynamic phase. Logistics company constructs its corporation factor network at urban and regional scales. Urban network includes the headoffice, operating department and distribution center with different corporation functions or logistics functions. The headoffice is located at urban centre, the distribution centre tends to be in the suburbs of a city, and the operating department is situated in the regions with many logistics activities. Regional network includes headquarter, regional headoffice, local branch, local office and operating department with different corporation functions or logistics functions. Corporation headquarter tends to be located in large cities, regional headoffice is generally at a political-economic centre in each logistics operating region, local branches are concentrated in capital city, economic centre and transport hub. Operating network of logistics activities comprises scheduled transport line, distribution system and logistics network. Transport line is the primary operating way of logistics activities which includes trunk and branch transport lines. Distribution system helps logistics company to transfer the cargoes throughout the country and improve its market competition with the development of regional distribution centre, urban regional distribution centre and urban distribution centre. The optimization, amalgamation and intertexture of scheduled transport line and logistics distribution system can develop into the primary operating mode of logistics network, namely hub-and-spoke system.