Showing papers on "Distribution center published in 2015"

City logistics for perishable products. The case of the Parma's Food Hub

Abstract: This paper analyzes schemes for delivering food to urban food outlets, i.e. corporate retail chains, independent retailers and the hotel, restaurants and catering (Ho.Re.Ca.) sector. We present a case study of Parma, Italy, where traffic regulations, delivery services and an urban distribution center have been implemented in order to improve efficiency and reduce the adverse impacts of urban food distribution within the city. The study depicts the role of public actors in defining policy measures and, in particular, focuses on the wholesale produce market, which has been revitalized by means of the Food Hub concept to provide consolidation services as an urban distribution center. Finally, we propose generalization to place our findings in the wider context of European city logistics studies.

Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning

Abstract: This paper proposes a deterministic mixed integer linear programming (MILP) model for downstream petroleum supply chain (PSC) network to determine the optimal distribution center (DC) locations, capacities, transportation modes, and transfer volumes. The model minimizes multi-echelon multi-product cost along the refineries, distribution centers, transportation modes and demand nodes. The relationship between strategic planning and multimodal transportation is further elucidated. A case study was considered with real data from the U.S. petroleum industry and transportation networks within Geographic Information System (GIS). A scenario analysis is also conducted to demonstrate the impact of key parameters on PSC decisions and total cost.

Method and system for order fulfillment in a distribution center

Abstract: Order allocation techniques pertaining to stops that a container makes in the process of fulfilling a customer order is disclosed. In one embodiment, this is accomplished by first identifying a pod that stocks the largest number of different items in a customer order. Then, a second pod is identified that stocks the largest number of remaining items in the customer order. The collection of pods defines a container path through the distribution center.

Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization-genetic algorithm

Abstract: A logistics distribution region partitioning model is developed.This model is to minimize the cost of two-echelon logistics distribution network.A hybrid algorithm with PSO and GA is proposed.The empirical results reveal that EPSO-GA algorithm outperforms other algorithms. Two-echelon logistics distribution region partitioning is a critical step to optimize two or multi-echelon logistics distribution network, and it aims to assign distribution unit to a certain logistics facility (i.e. logistic center and distribution center). Given the partitioned regions, vehicle routing problem can be further developed and solved. This paper established a model to minimize the total cost of the two-echelon logistics distribution network. A hybrid algorithm named as the Extended Particle Swarm Optimization and Genetic Algorithm (EPSO-GA) is proposed to tackle the model formulation. A two-dimensional particle encoding method is adopted to generate the initial population of particles. EPSO-GA combines the merits of Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) with both global and local search capability. By updating the inertia weight and exchanging best-fit solutions and worst-fit solutions between PSO and GA, EPSO-GA algorithm is able to converge to an optimal solution with a reasonable design of termination and iteration rules. The computation results from a case study in Guiyang city, China, reveal that EPSO-GA algorithm is superior to the other three algorithms, Hybrid Particle Swarm Optimization (HPSO), GA, and Ant Colony Optimization (ACO), in terms of the partitioning schemes, the total cost and number of iterations. By comparing with the exact method, the proposed approach demonstrates its capability to optimize a small scale two-echelon logistics distribution network. The proposed approach can be readily implemented in practice to assist the logistics operators reduce operational costs and improve customer service. In addition, the proposed approach is of great potential to apply in other research domains.

A novel multi-objective meta-heuristic model for solving cross-docking scheduling problems

Abstract: Cross-docking is a material handling technique in supply chain management.We consider multi-objective mathematical modeling for solving cross-docking problems.We propose genetic algorithm and particle swarm optimization to solve the problem.We minimize the make-span, transportation cost and the number of truck trips. Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This process minimizes the storage and order-picking functions in a warehouse. In this paper, we consider cross-docking in a supply chain and propose a multi-objective mathematical model for minimizing the make-span, transportation cost and the number of truck trips in the supply chain. The proposed model allows a truck to travel from a supplier to the cross-dock facility and from the supplier directly to the customers. We propose two meta-heuristic algorithms, the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective particle swarm optimization (MOPSO), to solve the multi-objective mathematical model. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example. The numerical results show the relative superiority of the NSGA-II method over the MOPSO method.

Optimal design of multi-echelon supply chain networks under normally distributed demand

Abstract: This paper addresses the optimal design of a multiproduct, multi-echelon supply network under uncertainty of demand. The network consists of multiproduct production sites, warehouses and distribution centers and decisions about the selection of facilities and their capacity are taken. Furthermore, information about the flows of products transferred and the safety stock at each distribution center is derived. The lead time of an order to a customer is computed, using the probabilities of overstocking and understocking. All these decisions are incorporated into a single period mixed integer non-linear programming problem (MINLP) which minimizes cost. Linearization techniques for selected highly non-linear terms of the models are explored in order to reduce the computational effort for the solution of the model. Finally, a sensitivity analysis is performed by changing product demand parameters and assessing their effect on the supply chain structure.

Demand Forecasting for Inventory Control

Abstract: Management is continually faced with a fast-paced flow of business planning and decision-making situations. A forecast of some type is used as a basis to meet many of these needs, whereby, the more reliable the forecasts , the better the outcome for the planning and decisions. Forecasting has plagued management for centuries, but now, with the advancement in computers, forecasting methods that previously were impossible to explore are currently achievable.

A Methodology to Exploit Profit Allocation in Logistics Joint Distribution Network Optimization

Abstract: Logistics joint distribution network (LJDN) optimization involves vehicle routes scheduling and profit allocation for multiple distribution centers. This is essentially a combinational and cooperative game optimization problem seeking to serve a number of customers with a fleet of vehicles and allocate profit among multiple centers. LJDN routing optimization based on customer clustering units can alleviate the computational complexity and improve the calculation accuracy. In addition, the profit allocation mechanism can be realized based on cooperative game theory through a negotiation procedure by the Logistics Service Provider (LSP). This paper establishes a model to minimize the total cost of the multiple centers joint distribution network when each distribution center is assigned to serve a series of distribution units. An improved particle swarm optimization (PSO) algorithm is presented to tackle the model formulation by assigning distribution centers (DCs) to distribution units. Improved PSO algorithm combines merits of PSO algorithm and genetic algorithm (GA) with global and local search capabilities. Finally, a Shapley value model based on cooperative game theory is proposed to obtain the optimal profit allocation strategy among distribution centers from nonempty coalitions. The computational results from a case study in Guiyang city, China, suggest the optimal sequential coalition of distribution centers can be achieved according to Strictly Monotonic Path (SMP).

Logistics distribution management method

Abstract: The invention discloses a logistics distribution management method which comprises steps as follows: goods owners upload goods source information to a logistics management center through operating terminals, vehicle owners unload vehicle source information to the logistics management center through intelligent mobile terminals, a monitoring module of the logistics management center matches the goods source information of the goods owners with the vehicle source information of the vehicle owners to recommend optimal goods sources and optimal vehicle sources, the vehicle owners plan out optimal transportation routes through a GPS (global positioning system) navigation system and perform real-time navigation, the vehicle owners and clients inquire in a logistics management platform to know real-time positions of goods, the vehicle owners generate electronic signatures and delivery information through the intelligent mobile terminals and upload the electronic signatures and the delivery information to the logistics management center after delivering the goods, and the logistics management center counts the transportation volume and sends logistics transportation management assessment information to the goods owners and the vehicle owners. With the adoption of the management method, management and matching by a logistics distribution center are more flexible, the success rate and effectiveness of logistics distribution are greatly increased, expenses of the goods owners and the vehicle owners are saved, and the service level is improved.

Logistics chains in freight transport modelling

Abstract: The flow of trade is not equal to transport flows, mainly due to the fact that warehouses and distribution facilities are used as intermediary stops on the way from production locations to the points of consumption or further rework of goods. This thesis proposes a logistics chain model, which estimates empirically valid transport flows necessary to ship the goods from production to consumption locations, emphasizing a proper modeling of flows related to warehouses and distribution centers.

Evaluation of Urban Distribution Centers Using Multiagent Modeling with Geographic Information Systems

Abstract: Current barriers to maintaining economies of scale for delivery include far distances of the depots from customers, road usage restrictions, customers’ delivery requests, and social, environmental, and economic costs. In many developed and developing countries, the effects of urbanization have increased city population. Such migration to cities is also attracting more movement of commodities into the city center. This research aimed to study the effectiveness and viability of urban distribution centers from a tactical viewpoint of planning for city logistics. A multiagent modeling approach with geographical information system support was used to test an urban distribution center (UDC) in Osaka City, Japan. The key findings from this research concluded that the UDC has potential for emissions reduction, but sustainability of the UDC is reliant on the UDC charges and carriers’ sensitivity to the rate of charges.

Selection of logistics distribution center location for SDN enterprises

Abstract: The location selection of the logistics distribution center for a supply and demand network (SDN) enterprises directly affected the efficiency of the logistics system operation and the customer ser...

Integrated Location-Production-Distribution Planning in a Multiproducts Supply Chain Network Design Model

Abstract: This paper proposes integrated location, production, and distribution planning for the supply chain network design which focuses on selecting the appropriate locations to build a new plant and distribution center while deciding the production and distribution of the product. We examine a multiechelon supply chain that includes suppliers, plants, and distribution centers and develop a mathematical model that aims at minimizing the total cost of the supply chain. In particular, the mathematical model considers the decision of how many plants and distribution centers to open and where to open them, as well as the allocation in each echelon. The LINGO software is used to solve the model for some problem cases. The study conducts various numerical experiments to illustrate the applicability of the developed model. Results show that, in small and medium size of problem, the optimal solution can be found using this solver. Sensitivity analysis is also conducted and shows that customer demand parameter has the greatest impact on the optimal solution.

Measuring the impact of stock-keeping unit attributes on retail stock-out performance

Abstract: Stock-outs are one of a retail chains’ biggest problems because they lead directly to lost sales, reduced profits, and the potential loss of customers This research applied probit regression to determine the relationship between various stock-keeping unit (SKU) attributes and retail stock-out performance The data sample came from a large grocery retailer in Serbia and included two high-risk product categories consisting of a total of 115 SKUs and 98 stores For the identification of stock-outs, a perpetual inventory aggregation method was used Regardless of the category observed, the variables that were identified as having a detrimental impact on stock-out performance include stock-out at the distribution center, promotion, and high sales speed On the other hand, a beneficial effect in terms of a reduced number of stock-outs was observed when the ordering process was performed using an automated ordering system

Execution Quality: An Analysis of Fulfillment Errors at a Retail Distribution Center

Abstract: Purchase orders specify many aspects of the fulfillment process, including item quantity, delivery time, carton labeling, bar coding, electronic data interchange, retail ticketing, and others. These fulfillment terms are instrumental for highly optimized supply chains employing automation and techniques such as pack-by-store. When fulfilling a purchase order, a supplier may commit a fulfillment error, i.e., the supplier may fail to adhere to the terms specified by the relevant contract. We present a study of the fulfillment errors that occur in practice using data collected from a major retailer's distribution center. While fulfillment errors involving incorrect product quantities and delivery times have received the most attention in the literature, we find that the majority of fulfillment errors in the context we study involve documentation, bar coding, and retail ticketing. We refer to these as correctable fulfillment errors, since they are amended at the retailer's distribution center through rework without coordination with the supplier. Using the retailer's data, we develop a simulation to assess the cost of these correctable fulfillment errors to the retailer's inventory system. Our research provides guidance to managers in identifying products and suppliers that impose large fulfillment error costs as well as in setting appropriate chargebacks for fulfillment errors.

An RFID solution for the monitoring of storage time and localization of perishable food in a distribution center

Abstract: In this research we adopt a design-science approach to propose an RFID-based solution that addresses the issue of short life-time of perishable food in the distribution center of a Logistics company. Various design alternatives are explored and assessed against the system requirements and constraints to illustrate how an RFID-based solution can effectively tackle the short storage-life problem. A prototype system is developed and evaluated. The proposed system monitors the storage time of perishable food items that are placed on tagged pallets in the warehouse and triggers alerts before the maximum storage-time is reached. We also discuss a solution for the localization of a pallet whose food content has nearly reached it maximum storage time. Design principles for developing appropriate systems to minimize the loss of perishable food during their storage at the warehouse are proposed and these can act as best practices for practitioners.

A hybrid fuzzy approach for the closed-loop supply chain network design under uncertainty

Abstract: A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper a CLSC network is investigated that involves four echelons in a forward direction including suppliers, manufacturer, distribution center and demand market, and three echelons in a backward direction including disposal, rework and collection centers. This paper presents a bi-objective model in order to design a network of bi-directional facilities in logistics network under uncertainties. Its objectives are to minimize the total costs as well as the total defective rate, disposal rate and pollution production rate. To solve the model, a hybrid solution approach is applied that combines fuzzy possibilistic programming and fuzzy multi-objective programming. Furthermore, in order to illustrate the validity of the model and applicability of the proposed solution approach, numerical experiments and the related sensitivity analysis are provided. Finally, the conclusion is provided.

Vehicle Routing Problem with Simultaneous Delivery and Pickup for Cold-chain Logistics

Abstract: In View of the vehicle routing problem with simultaneous delivery and pickup (VRPSDP) for cold-chain logistics, this paper analyzed the cost structure of vehicle fixed cost, running cost, refrigerating cost and cold-chain goods deteriorating cost in the process of delivery and pickup. By minimizing the total cost and integrating the delivery and pickup operation in cold chain logistics, an optimization model of VRPSDP for cold-chain logistics with a single distribution center and multiple client nodes was established. A genetic algorithm was designed to solve the problem. The results of empirical analysis verify that the established model and its algorithms are feasible and effective.

Delayed order delivery fulfillment

Abstract: Techniques and system configurations for order tracking and delivery fulfillment in an electronic commerce setting is described herein. In one example, a shipment that originates from a distribution center of a retailer is identified for delay (e.g., a delayed shipment in transit via a national carrier). The delayed shipment is replaced with a substitute shipment from inventory at an in-store location of the retailer. The substitute shipment is selected from an in-store location of the retailer based on proximity to the shipping destination, and is delivered via courier or agent to meet or precede a promised delivery date. The delayed shipment is then intercepted or redirected to the shipping source, the in-store location, or a distribution center. Related techniques for the management, processing, and tracking of data and information associated with substitute shipments are further described herein.

(R, s, S) inventory control policy and supplier selection in a two-echelon supply chain: an optimization via simulation approach

Abstract: Existing literature proves that Optimization via Simulation (OvS) is relatively easy to develop regardless of the complexity of the problem and provide a much more realistic solution methodology without assumption. Hence, we used OvS to determine optimal (R, s, S) policy for Distribution Center (DC)s and suppliers and to properly select the suppliers for DCs under stochastic environmental condition and lost sales system. Determining the optimal parameters, especially determining reorder point and order-up-to level, are major challenges for (R, s, S) policy and hence, their optimal values are determined by means of OvS. Also, initial inventories of DCs and suppliers are considered because the initial conditions of a simulation are crucial aspects of simulation modeling. The proposed OvS model can be helpful for managers to understand better the scope of both the problem at hand and opportunities associated with inventory management.

A Hybrid Analytic Hierarchy Process for Clustering and Ranking Best Location for Logistics Distribution Center

Abstract: Facility location decisions play a critical role in the strategic design of supply chain networks. This paper discusses facility location problem with focus on logistics distribution center (LDC) in Balkan Peninsula. Methodological hybrid Analytical Hierarchy Process (AHP) and k-means method is proposed here and it is shown how such a model can be of assistance in analyzing a multi criteria decision-making problem. This research represents a continuation of two existing studies: (1) PROMETHEE II ranking method; and (2) combine Greedy heuristic algorithm and AHP. The experimental results in our research could be well compared with other official results of the feasibility study of the LDC located in Balkan Peninsula.

Inventory management optimization model with database synchronization through internet network (A simulation study)

Abstract: In the past (classical supply chain) the supply of goods generally flow starts from factory or producer, then producer sent to a storage area called the warehouse. When finished goods are collected, the goods from storage area or warehouse (WH) is distributed to the distribution center (DC). Then after the goods were placed in the Distribution center, then the goods are shipped to the retailer (retailer). The drawback of this system is when there is a shortage of goods at the retail level, it takes a long time in the distribution of goods, from warehouse into the retailer. With the approach of the Physical Internet (PI), where the objective is to combine into a unified logistics network, the system is inter connected, the inventory can be shared through hubs that serve the market and distribution of resources. In other way, the function of warehouse and distribution center was replaced by hubs that serve to optimize transport and inventory. Although the physical internet inventory control model better than the classical model, but the model of inventory management with database synchronization better than the physical Internet. With the aproach database synchronization, several hubs can be combined into one hubs, and the plant can also sending goods directly to the retailer. In addition to optimizing transport and inventory, this analysis allows to choose a dynamic source when an order is placed: source substitution. Although this calculation is working on a computer simulation, the main intent of this paper is to define new research model inventory controlling better than classical inventory model and physical internet inventory model, which is inventory management model in synchronized database.

Associated logistics transportation optimized dispatching method with time-varying demand

Abstract: The invention relates to a time-varying demand associated logistics transportation optimized dispatching method based on a bee colony algorithm. The method comprises the specific implementation steps that (1) a distribution center acquires known demand information of a client; (2) an initial solution is constructed; (3) optimization is performed on the initial solution through an artificial bee colony algorithm based on taboo table thought; (4) a pre-loop passing through all the vertexes of a complete undirected graph G is obtained; (5) the distribution center collects time-varying information and acquires demand information of the time-varying client; (6) the pre-loop is adjusted according to a certain rule, and constraint conditions are satisfied; (7) the process is ended. According to the method, a final dispatching scheme based on time-varying demand associated with transportation dispatching is obtained.

Related logistics transportation optimized dispatching method with time-varying time window

Abstract: The invention relates to a related logistics transportation optimized dispatching method with a time-varying time window. The related logistics transportation optimized dispatching method with the time-varying time window comprises the specific following steps of 1 obtaining demand information of a reservation client through a distribution center; 2 performing initial path planning on the known client through a II insertion method; 3 improving a bee algorithm and optimizing an initial path based on a differential evolution algorithm; 4 collecting time varying information through the distribution center, obtaining new time window information of the client and recording application time of the new time window of the client; judging a key point at the time when the new information comes; 6 inserting the time-varying client to the initial path which is to be solved in the step 3 through the improved II insertion method to achieve optimization of the time-varying path; 7 ending. According to the related logistics transportation optimized dispatching method with the time-varying time window, a final dispatching scheme for related logistics transportation dispatching with the time-varying time window is obtained.

A Comparative Assesment of Facility Location Problem via fuzzy TOPSIS and fuzzy VIKOR: A Case Study on Security Services

Abstract: Today, law enforcement and security services are critically important for peace and prosperity of communities. The law enforcement forces serve citizens using security materials. The distribution of security materials is the dominant factor in determining the outcome of law enforcement duties. Failing to supply the required amounts of security materials properly, when and where it is needed, can lead to chaos. In this study, it is aimed to provide a decision support tool that can help to select the most appropriate location of security materials distribution center. The distribution center location problem is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. We proposed a comparative analysis that exploits fuzzy TOPSIS and fuzzy VIKOR techniques. Fuzzy weights of the 20 criteria and fuzzy judgments about 4 potential locations of distribution center as alternatives are employed to compute evaluation scores and ranking. Based on the evaluation criteria, Konya has been found the best alternative accourding to both techniques as well.