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Put it in the bag: Order fulfillment with a pocket sorter system
Abstract
Due to high real estate costs in urban areas, shop floor space is scarce in most brick‐and‐mortar stores. Maneuvering newly arrived merchandise through narrow aisles during shelf replenishment is time‐consuming for the sales staff and impedes customers. Therefore, many retail chains nowadays aim for store‐friendly shipments (SFS). By mirroring the layout of a store in the buildup of its dedicated shipments, the need for a zigzag movement through the store when replenishing shelves can be avoided. On the negative side, however, additional effort arises in the distribution centers. A suitable warehousing system to assemble SFS without excessive effort is a pocket (or pouch or bag) sorter, where each item is put into its separate bag. These bags, filled with items, are automatically transported while hanging from an overhead conveyor and can be sorted into any sequence before being delivered to the workstations that build SFS. This article investigates the assembly of SFS with a pocket sorter and presents scheduling procedures to enhance the efficiency of this process for a given set of store orders. We demonstrate that, despite its notorious complexity, the problem can be solved by simple decision rules with good performance. In a case study, we show that this approach can dramatically reduce the completion times of store orders, resulting in savings of more than 60% of the total working hours compared to a simple real‐world policy. Another 30% of reduction can be obtained by standardized store layouts.
Product proliferation and changes in demand require that retailers regularly determine how items should be allocated to retail shelves. The existing shelf‐space literature mainly deals with regular retail shelves onto which customers only have a frontal perspective. This paper provides a modeling and solution approach for two‐dimensional shelves. These are categories that are kept on tilted shelves. Customers have a total perspective on these shelves and can observe units of one particular item horizontally and vertically instead of just seeing the foremost unit of an item, as is the case of regular shelves. We develop a decision model that optimizes the two‐dimensional shelf‐space assignment of items to a restricted, tilted shelf. We contribute to current literature by integrating the assortment decision and accounting for stochastic demand, space elasticity and substitution effects in the setting of such self types. To solve the model, we implement a specialized heuristic that is based on a genetic algorithm. By comparing it to an exact approach and other benchmarks, we prove its efficiency and demonstrate that results are near‐optimal with an average solution quality of above 99% in terms of profit. Based on a numerical study with data from one of Germany's largest retailers, we were able to show within the scope of a case study that our approach can lead to an increase in profits of up to 15%. We demonstrate with further simulated data that integration of stochastic demand, substitution and space elasticity results in up to 80% higher profits.
Global trends such as just-in-time, containerization, and e-commerce have led to an ever increasing freight volume to be transported under tight delivery schedules. Many supply chains, thus, apply fully-automated sorting systems as one basic component of their distribution processes. Examples range from baggage handling in airports, over parcels sorted by tilt tray conveyors in distribution centers of the postal service industry, up to batches of picking orders isolated in the warehouses of e-commerce retailers. This paper surveys the scientific literature on all kinds of fully-automated conveyor-based sorting systems from an operational research perspective. We describe the wide range of applications and their different sorting systems, define their joint decision problems to be solved when designing and operating a sorter, review the literature, and identify future research challenges.
We consider the problem of resequencing a set of prearranged jobs when there is limited rese-quencing flexibility and sequence dependent changeover costs. Resequencing flexibility is limited by how far forward or backward a job can shift in the sequence relative to its original position. We show how the problem can be solved using dynamic programming in time polynomial in the number of jobs. We also show how the same solution approach can be extended to problems where sequencing constraints are job-specific and to problems where job features, which deter-mine changeover costs, are jointly determined with the job sequence. We provide an integer programming formulation to the resequencing problem whose linear programming relaxation offers a useful lower bound. We also describe a family of decomposition heuristics that are easy to customize to provide desired levels of solution quality and solution time. We document the quality of the lower bound from the linear programming relaxation and the upper bound from the heuristic using numerical results. We also provide numerical results to support manage-rial insights regarding the value of flexibility. We show that the value of flexibility is of the diminishing kind with most of the benefit realized with relatively limited flexibility. We also show that a balanced allocation of flexibility among forward and backward position shifting is superior to an unbalanced one. More significantly, we show that forward and backward posi-tion shifting flexibility are complements with the value of one increasing in the amount of the other. Finally, we apply our solution approach to a real world case from the automotive industry.
The car sequencing problem determines sequences of different car models launched down a mixed-model assembly line. To avoid work overloads of workforce, car sequencing restricts the maximum occurrence of labor-intensive options, e.g., a sunroof, by applying sequencing rules. We consider this problem in a resequencing context, where a given number of buffers (denoted as pull-off tables) is available for rearranging a stirred sequence. The problem is formalized and suited solution procedures are developed. A lower bound and a dominance rule are introduced which both reduce the running time of our graph approach. Finally, a real-world resequencing setting is investigated.
Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
Automated Storage and Retrieval Systems (AS/RSs) are warehousing systems that are used for the storage and retrieval of products in both distribution and production environments. This paper provides an overview of literature from the past 30 years. A comprehensive explanation of the current state of the art in AS/RS design is provided for a range of issues such as system configuration, travel time estimation, storage assignment, dwell-point location, and request sequencing. The majority of the reviewed models and solution methods are applicable to static scheduling and design problems only. Requirements for AS/RSs are, however, increasingly of a more dynamic nature for which new models will need to be developed to overcome large computation times and finite planning horizons, and to improve system performance. Several other avenues for future research in the design and control of AS/RSs are also specified.
There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom
in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given
function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization
of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and
provides an unfamiliar perspective on traditional optimization problems and methods.
Motivated by recent claims on the potential value of integration in warehouse management, this study evaluates the benefits arising from integrating the planning of order picking and packing processes in e-commerce warehouses. A set of research questions are proposed for exploring various benefits under different operational conditions and an experimental study is designed to answer them. In order to have a concrete model to represent the integrated planning method, a mixed-integer nonlinear programming model is developed, and then compared against a non-integrated variation. The experimental study makes the comparisons by analysing the collected empirical data from a real-life warehouse. Our findings indicate that integrated picking and packing planning can yield improved performance in different aspects under different configurations of objectives, order quantities, order categories or workforce allocation.
Warehouses are an inevitable component in any supply chain and a vividly investigated object of research. Much attention, however, is absorbed by warehousing systems dedicated to the special needs of online retailers in the business-to-consumer segment. Due to the ever increasing sales volumes of e-commerce this focus seems self-evident, but a much larger fraction of retail sales are still realized by traditional brick-and-mortar stores. The special needs of warehouses servicing these stores are focused in this paper. While e-commerce warehouses face low-volume-high-mix picking orders, because private households tend to order just a few pieces per order from a large assortment, distribution centers of retail chains rather have to process high-volume-low-mix orders. We elaborate the basic requirements within both business segments and identify suited warehousing systems for brick-and-mortar stores (e.g., fully-automated case picking). The setup of each identified warehousing system is described, elementary decision problems are discussed, and the existing literature is surveyed. Furthermore, we identify future research needs.
Robotic handling systems are increasingly applied in distribution centers. They require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. This makes them particularly fit for e-commerce operations. This paper reviews new categories of automated and robotic handling systems, such as shuttle-based storage and retrieval systems, shuttle-based compact storage systems, and robotic mobile fulfillment systems. For each system, we categorize the literature in three groups: system analysis, design optimization, and operations planning and control. Our focus is to identify the research issue and operations research modeling methodology adopted to analyze the problem. We find that many new robotic systems and applications have hardly been studied in academic literature, despite their increasing use in practice. Because of unique system features (such as autonomous control, flexible layout, networked and dynamic operation), new models and methods are needed to address the design and operational control challenges for such systems, in particular, for the integration of subsystems. Integrated robotic warehouse systems will form the next category of warehouses. All vital warehouse design, planning, and control logic, such as methods to design layout, storage and order-picking system selection, storage slotting, order batching, picker routing, and picker to order assignment, will have to be revisited for new robotized warehouses.
The online-to-offline (O2O) community supermarket is currently a popular O2O business
model in China. Owing to the small lot-size, high frequency, time-sensitive, and dynamic
arrival of online customer orders, many O2O community supermarkets face challenges in how to pick up the dynamic arrival orders and deliver them to customers with minimum makespan and delivery cost. To achieve the global optimal order fulfillment performance, we study the online integrated order picking and delivery problem for O2O community supermarket, and order pickers’ learning effects are considered to better plan the integrated problem. To propose a feasible and efficient schedule, the online algorithm 𝐀 is established, and the competitive ratio is proved to be 2 theoretically. To further verify the effectiveness and efficiency of algorithm 𝐀 in practice, we summarize the actual order fulfillment rules (named 𝐀𝟏), and conduct numerical experiments to compare algorithms 𝐀 with 𝐀𝟏. Moreover order pickers’ workforce characteristics are varied to evaluate the learning effects on the order fulfillment process. The results show that Algorithm 𝐀 performs better than 𝐀𝟏 in different situations, and considering pickers’ learning effects is significant for the accuracy and predictability of order fulfillment process.
E-commerce retailers face the challenge to assemble large numbers of time-critical picking orders each consisting of just a few order lines with low order quantities. Traditional picker-to-parts warehouses are often ill-suited for these prerequisites, so that automated warehousing systems (e.g., automated picking workstations, robots, and AGV-assisted order picking systems) are applied and organizational adaptions (e.g., mixed-shelves storage, dynamic order processing, and batching, zoning and sorting systems) are made in this branch of industry. This paper is dedicated to these warehousing systems especially suited for e-commerce retailers. We discuss suited systems, survey the relevant literature, and define future research needs.
Purpose
Given the progressive growth of e-commerce sales and the rising interest in omni-channel (OC) retailing amongst academics and practitioners, the purpose of this paper is to provide an up-to-date literature review on the logistics involved when moving towards OC retailing. Specifically, we have examined the main issues relating to e-fulfilment and distribution, highlighting how the topic has been developed over time, and identifying the most promising research streams for the near future.
Design/methodology/approach
A systematic literature review methodology is adopted. The review is based on 58 papers published from 2002 to 2017 in 34 international journals. The papers were analysed and categorised according to their defining characteristics, methodologies adopted and themes addressed.
Findings
This paper provides an overview of the main issues relating to e-fulfilment and distribution experienced by companies shifting towards OC, mapped along three dimensions: distribution network design, inventory and capacity management, delivery planning and execution. Despite the growing interest in OC retailing, many key topics are still under-represented, including the evolution of retail distribution networks, assortment planning over multiple channels, the logistics role played by stores in the delivery process and the interplay between different logistics aspects.
Originality/value
The paper offers insights into the main logistics issues in MC and OC retailing, as well as highlights potential fields for further investigation. From a managerial perspective, this paper is useful for retailers adopting an OC approach to guide their future efforts concerning their business logistics model.
Warehouses deliver labor-intensive services to customers. Underperformance may result in high costs and unsatisfied customer demand. New market developments force warehouses to handle a large number of orders within tight time windows. To cope with this, order picking operations need to be optimized by solving a wide range of planning problems. Optimizing order picking planning problems sequentially may yield a suboptimal overall warehouse performance. Still, previous warehouse planning reviews focus on individual planning problems. This literature review differs by investigating combinations of multiple order picking planning problems. A state-of-the-art review and classification of the scientific literature investigating combinations of tactical and operational order picking planning problems in picker-to-parts systems is presented with the aim of determining how planning problems are related. Furthermore, this literature review aims to find excellent policy combinations and to provide guidelines how warehouse managers can benefit from combining planning problems, in order to design efficient order picking systems and improve customer service. Combining multiple order picking planning problems results in substantial efficiency benefits, which are required to face new market developments.
This paper addresses the scheduling of a single storage/retrieval machine (or crane) in automated storage/retrieval systems (ASRSs). A novel classification scheme is presented for precisely defining different versions of the crane scheduling problem, when varying the layout of the ASRS, the characteristics of the storage and retrieval requests, and the objective function. This classification scheme is then applied for presenting different (known and novel) exact algorithms and complexity proofs for a variety of crane scheduling problems, for reviewing the literature, and for identifying future research needs.
In its original form [KIR82], [ČER85] the simulated annealing algorithm is based on the analogy between the simulation of the annealing pf solids and the problem of solving large combinatorial optimization problems. For this reason the algorithm became known as “simulated annealing”. In condensed matter physics, annealing denotes a physical process in which a solid in a heat bath is heated up by increasing the temperature of the heat bath to a maximum value at which all particles of the solid randomly arrange themselves in the liquid phase, followed by cooling through slowly lowering the temperature of the heat bath. In this way, all particles arrange themselves in the low energy ground state of a corresponding lattice, provided the maximum temperature is sufficiently high and the cooling is carried out sufficiently slowly. Starting off at the maximum value of the temperature, the cooling phase of the annealing process can be described as follows.
Almost ever since freight has been transported via rail, shunting yards (also called classification or marshaling yards) are operated in order to separate freight trains and reassemble new trains. The efficient use of shunting yards has a deep impact on the efficiency and reliability of rail freight services. Thus, much research on shunting yards has been published, starting from the 1950s. Lately, several publications mostly focusing on the sorting procedures have livened up research on shunting yards. This paper reviews the literature on the operational processes at shunting yards over the last 40 years and discusses the operational challenges of freight transshipment. The approaches are classified according to different sorting strategies which allows an easy access to the models for both, researchers and practitioners. The paper concludes with an overview on future research challenges.
Procedures for improving the efficiency of classification yard operations are studied in this paper. Multistage sorting strategies make efficient use of land and tracks. Equations are derived giving the service time per car and space requirements of three multistage sorting strategies: the sorting-by-block, the sorting-by-train, and the triangular sorting strategies. Exact service time formulas are given for the first two strategies, and an approximation is given for the last strategy. The approximation, when compared with exact calculations, proved to be quite robust. Errors were on the order of one percent. Sensitivity analysis showed that the formulas are accurate when assumptions used in the approximations are not satisfied. A surprising finding was that the triangular sorting strategy, which allows many more classifications on a given set of tracks than the other two, does not require significantly greater service time in flat yards. Presently, the triangular strategy is not widely used in the U.S., in preference for the sorting-by-block strategy.
In this article, we study the train classification problem. Train classification basically is the process of rearranging the cars of a train in a specified order, which can be regarded as a special sorting problem. This sorting is done in a special railway installation called a classification yard, and a classification process is described by a classification schedule. In this article, we develop a novel encoding of classification schedules, which allows characterizing train classification methods simply as classes of schedules. Applying this efficient encoding, we achieve a simpler, more precise analysis of well-known classification methods. Furthermore, we elaborate a valuable optimality condition inherent in our encoding, which we succesfully apply to obtain tight lower bounds for the length of schedules in general and to develop new classification methods. Finally, we present complexity results and algorithms to derive optimal schedules for several real-world settings. Together, our theoretical results provide a solid foundation for improving train classification in practice. © 2010 Wiley Periodicals, Inc. NETWORKS, 2011 © 2011 Wiley Periodicals, Inc.
The theory of deterministic sequencing and scheduling has expanded rapidly during the past years. In this paper we survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory. Special cases considered are single machine scheduling, identical, uniform and unrelated parallel machine scheduling, and open shop, flow shop and job shop scheduling. We indicate some problems for future research and include a selective bibliography.
This paper gives an overview of recent research on the performance evaluation and design of carousel systems. We discuss picking strategies for problems involving one carousel, consider the throughput of the system for problems involving two carousels, give an overview of related problems in this area and present an extensive literature review. Emphasis has been given on future research directions in this area.
An extensive review on warehouse operation planning problems is presented. The problems are classified according to the basic warehouse functions, i.e., receiving, storage, order picking, and shipping. The literature in each category is summarized with an emphasis on the characteristics of various decision support models and solution algorithms. The purpose is to provide a bridge between academic researchers and warehouse practitioners, explaining what planning models and methods are currently available for warehouse operations, and what are the future research opportunities.
The resequencing and feature assignment problem (RFAP) appears among jobs in the assembly line, especially in the automotive industry. Each job in the assembly line must be assigned a feature from its feasible feature set. However, a changeover cost is incurred between two consecutive jobs with different features. To minimize the total changeover cost, the job sequence needs to be rearranged, but the rearrangement is restricted to the number of offline buffers. The RFAP turns out to be -hard in the strong sense. Based on a beam search heuristic to generate upper bounds of optimum solutions, we have proposed an iterative search scheme which can achieve optimum solutions in a reasonably short time, for cases sized as large as that in reality. Extensive experiments have shown very favourable results for our methods in terms of both the solution quality and the time efficiency.
Wave-based release policies are prevalent in warehouses with an automated sorter, and take different forms depending on how much waves overlap and whether the sorter is split for operating purposes. Waveless release is emerging as an alternative policy adopted by an increasing number of firms. While that new policy presents several advantages relative to waves, it also involves the possibility of gridlock at the sorter. In collaboration with a large US online retailer and using an extensive dataset of detailed flow information, we first develop a model with validated predictive accuracy for its warehouses operating under a waveless release policy. We then use that model to compute operational guidelines for dynamically controlling the main parameter of its waveless policy, with the goal of maximizing throughput while keeping the risk of gridlock under a specified threshold. Secondly, we leverage that model and dataset to perform through simulation a performance comparison of wave-based and waveless policies in this context. Our waveless policy yields larger or equal throughput than the best performing wave-based policy with a lower gridlock probability in all scenarios considered. Waveless release policies thus appear to merit very serious consideration by practitioners. Facilities using a non-overlapping wave policy should also consider overlapping waves or a split sorter policy.
Nowadays, mixed-model assembly lines are applied in a wide range of industries to mass-produce customized products to order, e.g., in automobile industry. An important decision problem in this context receiving a lot of attention from researchers and practitioners is the sequencing problem, which decides on the succession of workpieces launched down the line. However, if multiple departments with diverging sequencing objectives are to be passed or unforeseen disturbances like machine breakdowns or material shortages occur, a resequencing of a given production sequence often becomes equally essential. This paper reviews existing research on resequencing in a mixed-model assembly line context. Important problem settings, alternative buffer configurations, and resulting decision problems are described. Finally, future research needs are identified as some relevant real-world resequencing settings have not been dealt with in literature up to now.
This paper presents a detailed survey of the research on warehouse design, performance evaluation, practical case studies, and computational support tools. This and an earlier survey on warehouse operation provide a comprehensive review of existing academic research results in the framework of a systematic classification. Each research area within this framework is discussed, including the identification of the limits of previous research and of potential future research directions.
SSI Carrier -Flexibles Taschensorter-System für E-Commerce und Omnichannel
- Ssi Schäfer
SSI Schäfer. (2021). SSI Carrier -Flexibles Taschensorter-System für
E-Commerce und Omnichannel. https://www.youtube.com/watch?
v=JXy0Z4XuElU