Single Warehouse Research Articles

SWMR Algorithm Approach for the Vendor Managed Inventory Problem when Static Demand Rates

In a two-phase supply chain with Vendor Managed Inventory (VMI) policies, the supplier takes on the duty of keeping its retailers' inventory up to date and making sure they never run out of stock. This is in addition to his inbound inventory. This study aims to combine the retailers in various set partitions or to maximize their distribution and inventory holding costs within the same set partition. This paper focuses on a two-stage supply chain made of a single warehouse and multiple retailers (SWMR) facing a static demand and implementing VMI. We proposed a model for coordinating the system with a two-phase solution method. The first phase is to minimize the overall inventory costs and, in the second phase, a constructive vehicle routing problem (VRP) heuristic is used to optimize the distribution costs by satisfying some additional restrictions. Results of this implementation of VMI in an illustrative supply chain case are shown and discussed in detail.

Reduced food waste through inventory control despite throwing out food before expiration: Online vs. offline retail

Online retailers throw out food that has not yet expired. This gives rise to the question whether online retailers generate more food waste than offline retailers, who typically throw out food only after it has expired. We focus on the food waste at the retailer which inherently ensues from the logistical set-up. We provide a theoretical discussion of the potential increase in food waste as a result of the inventory control policy and throwing out food that has not yet expired, as is the case for online retailers. Note that the online retailer has some advantages over offline retailers as well. Online retailers benefit from full control of order picking, which is instead often done by the consumer in offline retail. Moreover, the online retailer often benefits from the pooling effect, as offline retailers might use multiple stores to satisfy the same demand volume as an online retailer from a single warehouse. Our numerical experiments with a base-stock policy suggests that online retail actually yields less food waste for many products, despite throwing out food before expiration.

Adaptive stochastic lookahead policies for dynamic multi-period purchasing and inventory routing

We explore a problem faced by agri-food e-commerce platforms in purchasing different, perishable products and collecting them from multiple producers and delivering them to a single warehouse, aiming to maintain adequate inventory levels to meet current and future customer demand, while avoiding waste. Customer demand and suppliers’ purchase prices and supply volumes are uncertain and revealed on a periodical basis. Every period, purchasing, inventory, and routing decisions are made to satisfy demand and to build inventory for future periods. For effective decisions integrating all three decision components and anticipating future developments, we propose a stochastic lookahead method that, in every period, samples future scenarios for demand, supply volumes, and prices. It then solves a two-stage stochastic program to obtain the decision for the current period. To make this approach computationally tractable, we reduce the routing decision in the two-stage program and use an approximate routing cost instead. Given the reduced decision, we then create the final decision via a conventional routing heuristic. We learn the routing cost approximation adaptively via repeated training simulations. In comprehensive experiments, we show that all three components, stochastic lookahead, routing cost approximation, and adaptive learning, are very effective individually, but especially in combination. We also provide a comprehensive analysis of the problem parameters and obtain valuable insights in problem and methodology.

A matheuristic for a multi-period three-echelon network design problem with temporary capacity acquisition

This study addresses a three-echelon network design problem that determines the location and size of new warehouses, the removal of company-owned warehouses, the inventory levels of multiple products at the warehouses, and the assignment of suppliers as well as customers to warehouses over a multi-period planning horizon. A distinctive feature of our problem is that new warehouses operate with modular capacities that can be expanded or reduced over several periods, the latter not necessarily having to be consecutive. Moreover, in every period, the demand of a customer for a given product has to be satisfied by a single warehouse. The problem arises in the context of warehousing-as-a-service, a business scheme that offers flexible conditions for temporary capacity leasing. The associated fixed warehouse lease cost reflects economies of scale in the capacity size and the length of the lease contract. We develop a mixed-integer linear programming formulation and propose a matheuristic to solve this problem, which exploits the structure of the optimal solution of the linear relaxation to successively assign customers to open warehouses and fix other binary variables related to warehouse operation. Additional variable fixing rules are also developed, based on a scheme for managing inventories at warehouses and using the product quantities provided by suppliers. Numerical experiments with randomly generated large-sized instances reveal that the proposed matheuristic outperforms a general-purpose solver in 74% of the instances by identifying higher quality solutions in a substantially shorter computing time.

Multi-objective optimization for perishable product dispatch in a FEFO system for a food bank single warehouse

One of the main challenges of food bank warehouses in developing countries is to determine how to allocate perishable products to beneficiary agencies with different expiry dates while ensuring food safety, meeting nutritional requirements, and minimizing the shortage. The contribution of this research is to introduce a new multi-objective, multi-product, and multi-period perishable food allocation problem based on a single warehouse management system for a First Expired-First Out (FEFO) policy. Moreover, it incorporates the temporal aspect, guaranteeing the dispatch of only those perishable products that meet the prescribed minimum quality standards. A weighted sum approach converts the multi-objective problem of minimizing a vector of objective functions into a scalar problem by constructing a weighted sum of all the objectives. The problem can then be solved using a standard constrained optimization procedure. The proposed mixed integer linear model is solved by using the CPLEX solver. The solution obtained from the multi-objective problem allows us to identify days and products experiencing shortages. In such cases, when there is insufficient available inventory, the total quantity of product to be dispatched is redistributed among beneficiaries according to a pre-established prioritization. These redistributions are formulated as integer programming problems using a score-based criterion and solved by an exact method based on dynamic programming. Computational results demonstrate the applicability of the novel model for perishable items to a real-world study case.

A Two-Warehouse Lot Sizing Problem for Defective Items with a Completely Backlogged Shortage Under Limited Storage Capacity for Rented Warehouses

Determining an economic order quantity across inventory management is vital for any production or distribution company. There is an assumption in classical lot-sizing problems that the inventories are stored in a single warehouse with unlimited capacity. However, the mentioned assumption may be unrealistic, and in many markets, owned warehouses (OW) have limited capacity, therefore, in some cases, a rented warehouse (RW) is considered for storing goods to create more flexibility in terms of space capacity. In this study, we proposed a more realistic extension of a two-warehouse system, which intends to investigate an optimal EOQ considering limited storage for both OW and RW. This paper contributes to considering multiple RWs with limited capacity. For this purpose, a two-objective MINLP lot-sizing problem with a discreet period and finite time horizon is taken into account. The complexity of the model is to determine if there is a need to rent one or multiple warehouses regarding limited storage on OWs and RWs as well as budget restrictions to hire one or multiple warehouses. Also, all parameters are considered to be stochastic which means they follow a specific probability distribution. As the capacity of RWs and the total available budget to rent them are random parameters, the constraint on budget, as well as RW’s capacity in a period, can be formulated as chance constraints. Finally, four multi-objective decision-making methods namely Goal programming, Lp-Metric, Goal Attainment, and Augmented E-Constraint are utilized to solve the concerned problem. Then, the best method is chosen based on graphical, statistical, and TOPSIS analysis. Moreover, the Lagrangian Relaxation method is applied since solving this optimization model in large-size problems requires a considerable amount of time. In the end, the effect of changing the rates of three parameters on objective function values is evaluated through sensitivity analysis.

Saving Concepts in Supply Chain Management: A Study on Inventory and Transportation Costs

Supply chain is a systematic and strategic coordination of the traditional business function to across business function within supply chain for the purpose of improving the long-term performance of the business. The objective of the paper is to understand the saving concepts are used in operational path to achieve optimization in term of cost saving. Business nowadays going towards to minimizing the operational in order to compete with others The purpose is to achieve the minimization in inventory routing problem (IRP) with cost minimization consists inventory and transportation costs focus on the single warehouse with multiple customers. The operational costs can be reduced by solving the inventory management and transportation process for vehicle to replenish the inventory. In this paper, a mathematical model was developed and simulated by using an optimization software package to achieve the optimization. The findings show that the optimization can be achieved by reducing the movement of the vehicle To conclude, the bigger the vehicle’s capacity, much capacity can add and less routes taken by the vehicle to supply the inventory to the customers.

Research on Multi-product Order Splitting and Distribution Route Optimization Of "Multi-warehouse in One Place"

In recent years, large online supermarkets have become a new trend in the development of e-commerce. Due to the limited storage capacity of a single warehouse, many large online supermarkets, such as Jingdong and Tmall, often adopt the warehouse layout of "one place and multiple warehouses" to quickly respond to customer needs, and the sorting and distribution tasks of orders are completed by the warehouse. At the same time, due to the change of people's lifestyle, customer demand presents the characteristics of "one order with multiple products" and "one order with multiple quantities", which makes the split fulfillment of orders become a common phenomenon. In this paper, under the condition that the warehouse is not out of stock in the layout of one place and many warehouses, aiming at the split execution problem of multi-category orders, the split order method is based on the combination of "minimum split order rate" and "principle of proximity". An order splitting optimization model considering both category and quantity splitting is established, and a set of initial order batch splitting schemes is formed to achieve the first optimization of multi-category order splitting. Secondly, the PLBH-LNS method is used to generate a better initial distribution scheme considering the customer preset time window limit and vehicle-mounted capacity constraint. Finally, with the goal of minimizing the total order performance cost, the solution idea of two-stage method is used for reference, based on the initial order splitting scheme and distribution scheme, the improved two-stage genetic algorithm is used to generate the optimal order allocation scheme and distribution scheme from the alternative schemes, and the global optimization of the splitting and distribution process is realized. The experimental results show that compared with the order splitting strategy using simple rules in practice, the PLBH-LNS method can reduce the average order splitting cost by 12.48%, which provides a new idea and effective auxiliary decision support for the order splitting problem of large online supermarkets.

Crowdsourced last mile delivery: Collaborative workforce assignment

In this paper, we propose a last mile delivery selection model using crowdsourced workers that optimizes the trade-off between cost, time, and workers’ performance. Most of the current methods utilize either greedy worker–task assignments or a task-by-task basis selection to reach a sufficient worker–task assignment. However, a better trade-off between the distance traveled and delivery time can be further obtained by considering the quality of performance on the tasks as a whole rather than treating tasks individually. As a solution, we present a novel framework for last mile delivery which separates the routing and assignment aspects of the problem and solves the assignment problem by maximizing the overall quality of the delivery. The Quality of Service (QoS) is defined as a non-linear function of the number of allocated tasks, distance traveled, timeliness of the delivery, workers’ reputation, and confidence in delivery completion. In the first step, the delivery tasks to be shipped from a single warehouse are clustered using k-medoids. The set of tasks in each cluster are to be delivered by the same worker. The shipping provider will send a truck to handover the corresponding parcels to each worker. Accordingly, the shortest route for the truck is computed using Tabu search, where the handover points to the potential workers are the centroids of the clusters. Tabu search is also used to compute the potential workers’ routes from the handover point through all the tasks in the cluster. Finally, genetic algorithm is used to effectively solve the assignment problem where each worker is assigned to several neighboring tasks. The performance of the proposed assignment mechanism is evaluated and compared to greedy solutions with respect to the QoS as well as its components. The results show that the proposed algorithm achieves 100% task allocation ratio while outperforming greedy selections in terms of QoS. Moreover, it is able to increase confidence in task completion by 20.3% on average and prevent delays to the schedule of the truck.

New Order-picking Routing Heuristics for Single Block Rectangular Warehouse

New Order-picking Routing Heuristics for Single Block Rectangular Warehouse

TAGOPSIN: collating taxa-specific gene and protein functional and structural information

BackgroundThe wealth of biological information available nowadays in public databases has triggered an unprecedented rise in multi-database search and data retrieval for obtaining detailed information about key functional and structural entities. This concerns investigations ranging from gene or genome analysis to protein structural analysis. However, the retrieval of interconnected data from a number of different databases is very often done repeatedly in an unsystematic way.ResultsHere, we present TAxonomy, Gene, Ontology, Protein, Structure INtegrated (TAGOPSIN), a command line program written in Java for rapid and systematic retrieval of select data from seven of the most popular public biological databases relevant to comparative genomics and protein structure studies. The program allows a user to retrieve organism-centred data and assemble them in a single data warehouse which constitutes a useful resource for several biological applications. TAGOPSIN was tested with a number of organisms encompassing eukaryotes, prokaryotes and viruses. For example, it successfully integrated data for about 17,000 UniProt entries of Homo sapiens and 21 UniProt entries of human coronavirus.ConclusionTAGOPSIN demonstrates efficient data integration whereby manipulation of interconnected data is more convenient than doing multi-database queries. The program facilitates for instance interspecific comparative analyses of protein-coding genes in a molecular evolutionary study, or identification of taxa-specific protein domains and three-dimensional structures. TAGOPSIN is available as a JAR file at https://github.com/ebundhoo/TAGOPSIN and is released under the GNU General Public License.

The Development of a Heterogeneous MP Data Model Based on the Ontological Approach

The article discusses the approaches providing symmetric access of all industrial production services to the data of business processes of the enterprise by building a single warehouse of heterogeneous data of a metallurgical production. The warehouse is a part of an automated statistic quality control system for the products of a metallurgical enterprise. The article describes an ontological storage model of data coming from various sources of information in the production process. The concept of “a unit of production of metallurgical production” is introduced that is the connecting component of the entire production life cycle of a metallurgical production. The authors propose an ontological model of the production process, in terms of information flows which are formed in an enterprise at each stage of production. Based on the constructed ontological model, the structure of recording an array of information in the heterogeneous data warehouse is justified and formed. Heterogeneous data warehouse forms a single information space of the enterprise, which serves as the basis for analytical analysis throughout the production and decision—making process. For example, timely response to the deviation reasons from the given physical and chemical properties of the finished product.

АСПЕКТЫ ИНТЕГРАЦИИ ИНФОРМАЦИОННЫХ СИСТЕМ СЕЛЬСКОХОЗЯЙСТВЕННЫХ ПРЕДПРИЯТИЙ

The authors of the article see the problem of digitalization of agriculture in the insufficient funding resources at the enterprises for the introduction of information and communication technologies, development of infrastructure in rural areas, shortage of IT-personnel, etc. The solution of these problems is facilitated by the integration of information systems, which is necessary to begin with the agricultural enterprises themselves. The paper notes the influence of external and internal factors on the improvement of agricultural business. Rosstat (Federal State Statistics Service) data on the agricultural enterprise performance and the use of special software are presented. Integration implies the implementation of the interconnection and interdependence of all parts of the system with the separation of the area of influence on each other, taking into account two features: structural levels and enterprise management functions. Design, development and use of a ready-made information system of the enterprise should include business logic, functional and user requirements for the system. As an integrated system, it is proposed to use ERP- systems based on the management of a single data warehouse containing all the necessary corporate information: production, financial, personnel, etc. An example of such a system is the 1C: ERP Agro-industrial Complex 2 software product, which takes into account the industry specifics of the agro-industrial complex enterprises and allows leveling sanction risks. Another important aspect of the problem under study is the use of information systems based on geo- information technologies providing information support for decision-making on the base of accumulated data of a digital terrain model, remote sensing of land, soil characteristics, use of land resources, monitoring of agricultural- purpose land. By increasing the scale, agricultural enterprises are able to meet their own domestic needs completely and enter international markets with environmentally safe quality products. Integrated information systems will provide them with effective assistance providing complete reliable information for making managerial decisions.

A电网企业单仓库补库模型应用及运行评价研究

A电网企业单仓库补库模型应用及运行评价研究

Optimization of product category allocation in multiple warehouses to minimize splitting of online supermarket customer orders

In an online supermarket, people may purchase multiple items in a single order for convenience or to obtain free delivery. Multi-item customer orders often need to be split into multiple shipments because the ordered items may be stored in different warehouses. Order splitting results in higher shipping costs. One way to reduce splitting is to store and retrieve all the items in a single warehouse. However, due to the vast volume of items sold by online supermarkets, it is difficult to build and operate such a warehouse. Another way is to optimize the allocation of products in multiple warehouses to reduce order splitting. In this paper, we propose a K-links heuristic clustering algorithm to optimize the product category allocation among multiple warehouses based on the distribution of multi-item orders to minimize the total number of order splits. Using online order and inventory data from a large Chinese online supermarket, we demonstrate that our algorithm performs well and dramatically reduces order splitting.

Fuzzy Random Chance-Constrained Programming Model for the Vehicle Routing Problem of Hazardous Materials Transportation

As an indispensable necessity in daily routine of citizens, hazardous materials (Hazmat) not only plays an increasingly important role, but also brings a series of transportation uncertainty phenomena, the most prominent of which is a safety problem. When it attempts to find the best vehicle route scheme that can possess the lowest risk attribute in a fuzzy random environment for a single warehouse, the influence of cost should also be taken into account. In this study, a new mathematical theory was conducted in the modeling process. To take a full consideration of uncertainty, vehicle travel distance and population density along the road segment were assumed to be fuzzy variables. Meanwhile, accident probability and vehicle speed were set to be stochastic. Furthermore, based on the assumptions, authors established three chance constrained programming models according to the uncertain theory. Model I was used to seek the achievement of minimum risk of the vehicle route scheme, using traditional risk model; the goal of Model II was to obtain the lowest total cost, including the green cost, and the main purpose of Model III was to establish a balance between cost and risk. To settle the above models, a hybrid intelligent algorithm was designed, which was a combination of genetic algorithm and fuzzy random simulation algorithm, which simultaneously proved its convergence. At last, two experiments were designed to illustrate the feasibility of the proposed models and algorithms.

Stress Analysis of Surrounding Rock of Rectangular Pipe Gallery in Mountain City

In this paper, the basic methods and principles of complex variable function to solve the excavation problem of caverns in single connected domain are studied. Based on the basic principle of conformal transformation and the engineering practicability, the problem of excavating rectangular section single warehouse pipe gallery in a single rock stratum is simplified as a semi-infinite plane rectangular hole problem. The rectangular hole problem is transformed into an equivalent circular hole by conformal transformation. A simplified calculation model of the extruding rectangle comprehensive pipe gallery is proposed and its surrounding rock stress calculation formula is deduced. Combined with the example of mountainous city comprehensive pipe gallery project, Theoretical calculation and numerical simulation show that the surrounding rock stress of the comprehensive pipe gallery is close, which verifies the applicability of the simplified formula. The structural design and construction design of rectangular integrated pipe gallery provide theoretical support. Comparing the stress of surrounding rock of different width pipe gallery, it is found that the stress concentration degree at the top corner of the rectangular pipe gallery increases with the increase of the width of the pipe gallery. The width of the excavation of the rectangular pipe gallery must be strictly controlled during construction.

Design and Verification of Outbound Mode Strategy Based on EIQ Analysis

In this paper, in view of the poor delivery efficiency of the warehouse, the theoretical analysis and mathematical modeling are closely linked by collecting and statistics data of a large number of data from single storehouse and single warehouse. The qualitative analysis and quantitative calculation are combined with a large number of actual data obtained by actual operation. Based on this, a discriminant model of the outgoing mode based on EIQ analysis is established to solve the data into the model. It can be seen from the verification results that the error of the time difference of the way out of the warehouse can be less than ±25 s, and it can be proved that the model is practical and reasonable in the selection decision for the way of out of the storehouse, and can provide reference for the selection of a batch order. Finally, the optimized scheme of the outlet of the solid warehouse is obtained, which improves the warehouse outgoing efficiency.

Increased flexibility in multi echelon multi capacitated supply chain network design

The multi echelon, multi capacitated supply chain network design challenge is to determine the numbers, locations and capacity levels of plants and warehouses; as well as the product flow from plants to warehouses and then from warehouses to customer zones in order to meet demand at minimum cost. Mathematical models for multi capacitated supply chain network design provide a finite set of capacity levels from which to choose; and include variables and constraints to ensure the selection of a single capacity level for each facility to be built. By eliminating the constraints that enforce a single capacity selection, we allow for the selection of several capacity levels for a single plant or warehouse. If such a selection occurs, the plant or warehouse is built with size equal to the sum of the selected capacity levels. This gives an exponential increase in the number of available capacity levels. The increased flexibility allows for less costly supply chain network designs. We present numerical results that demonstrate improved solutions, that is, lower cost supply chain network designs, with lower computational effort.

Sliding mode control of inventory management systems with bounded batch size

Abstract In this paper, variable structure control of discrete time systems is considered and the idea of reaching law based sliding mode control is presented. Then the idea is applied to design a control strategy for a class of supply chains with multiple suppliers. In the considered inventory management systems, goods are delivered to a single warehouse with limited capacity. Suppliers themselves have finite manufacturing capabilities, but are also not willing to accept orders of negligible size. The reaching law proposed for such systems ensures full satisfaction of the unpredictable consumers’ demand while adhering to state and input constraints.