1,112 research outputs found
Optimal Investment with Lumpy Costs
In this paper we solve a continuous-time model of investment with uncertainty, irreversibility and a broad class of lumpy adjustment costs. In addition to being general, our solution is quite tractable and intuitive. We show that, in contrast to standard results, the marginal value of capital jumps when investment is undertaken. We also find that firms facing higher uncertainty let their capital stock depreciate further before they invest, but increase their capital by a similar proportion once they do invest. We extend both the user cost and q theories of investment to incorporate lumpy investment. We confirm that with lumpy investment, a variant of Tobin's q can be a better predictor of investment than marginal q.
Optimal Storage Rack Design for a 3-dimensional Compact AS/RS
In this paper, we consider a newly-designed compact three-dimensional automated storage and retrieval system (AS/RS). The system consists of an automated crane taking care of movements in the horizontal and vertical direction. A gravity conveying mechanism takes care of the depth movement. Our research objective is to analyze the system performance and optimally dimension of the system. We estimate the crane’s expected travel time for single-command cycles. From the expected travel time, we calculate the optimal ratio between three dimensions that minimizes the travel time for a random storage strategy. In addition, we derive an approximate closed-form travel time expression for dual command cycles. Finally, we illustrate the findings of the study by a practical example.AS/RS;Warehousing;Order Picking;Travel Time Model;Compact Storage Rack Design
Design and Control of Warehouse Order Picking: a literature review
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 its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking 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.Order picking;Logistics;Warehouse Management
b anti-b Higgs production at the LHC: Yukawa corrections and the leading Landau singularity
At tree-level Higgs production in association with a b-quark pair proceeds
through the small Yukawa bottom coupling in the Standard Model. Even in the
limit where this coupling vanishes, electroweak one-loop effects, through the
top-Higgs Yukawa coupling in particular, can still trigger this reaction. This
contribution is small for Higgs masses around 120GeV but it quickly picks up
for higher Higgs masses especially because the one-loop amplitude develops a
leading Landau singularity and new thresholds open up. These effects can be
viewed as the production of a pair of top quarks which rescatter to give rise
to Higgs production through WW fusion. We study the leading Landau singularity
in detail. Since this singularity is not integrable when the one-loop amplitude
is squared, we regulate the cross section by taking into account the width of
the internal top and W particles. This requires that we extend the usual box
one-loop function to the case of imaginary masses. We show how this can be
implemented analytically in our case. We study in some detail the cross section
at the LHC as a function of the Higgs mass and show how some distributions can
be drastically affected compared to the tree-level result.Comment: 48 pages, 20 figures. Phys.Rev.D accepted version. Conclusions
unchanged, minor changes and references adde
Determining The Optimal Order Picking Batch Size In Single Aisle Warehouses
This work aims at investigating the influence of picking batch size to average time in
system of orders in a one-aisle warehouse under the assumption that order arrivals follow a
Poisson process and items are uniformly distributed over the aisle's length. We model this
problem as an M/G[k]/1 queue in which orders are served in batches of exactly orders. The
average time in system of the M/G[k]/1 queue is difficult to obtain for general service
times. To circumvent this obstacle, we perform an extensive numerical experiment on the
average time in system of the model when the service time is deterministic (M/D[k]/1) or
exponentially distributed (M/M[k]/1). These results are then compared with the corresponding
times in system of the actual model taken from simulation runs. A variance analysis is
carried out and its result elicits that the M/D/[k]/1 queue is a very good approximation for
the average time in system of orders. Correspondingly, the optimal picking batch size of the
real system ca
Optimal Storage Rack Design for a 3-dimensional Compact AS/RS
In this paper, we consider a newly-designed automated storage and retrieval system (AS/RS). The system consists of an automated crane taking care of movements in the horizontal and vertical direction. A gravity conveying mechanism takes care of the depth movement. The aim of the research was to facilitate the problem of optimal design and performance evaluation of the system. We estimate the crane’s expected travel time for single command cycles. From the expected travel time, we calculate the optimal ratio between three dimensions that minimize the travel time for a random storage strategy. Finally, we illustrate the findings of the study by a practical example
Determining Number of Zones in a Pick-and-pack Orderpicking System
In this study we consider a pick-to-pack orderpicking system, in which batches of orders are picked simultaneously from different(work) zones by a group of order pickers. After picking, the
orders are transported by a conveyor to the next station for packing. Our aim is to determine the optimal number of zones such that the overall (picking and packing) time to finish a batch is
minimized. We solve this problem by optimally assigning items to pick routes in each zone. We
illustrate the method with data taken from a distribution center of one of the largest online
retailers in the Netherlands
Travel Time Estimation and Order Barching in a 2-Block Warehouse
The order batching problem (OBP) is the problem of determining the number of orders to be picked together in one picking tour. Although various objectives may arise in practice, minimizing the average throughput time of a random order is a common concern. In this paper, we consider the OBP for a 2-block rectangular warehouse with the assumptions that orders arrive according to a Poisson process and the method used for routing the order-pickers is the well-known S-shape heuristic. We first elaborate on the first and second moment of the order-picker's travel time. Then we use these moments to estimate the average throughput time of a random order. This enables us to estimate the optimal picking batch size. Results from simulation show that the method provides a high accuracy level. Furthermore, the method is rather simple and can be easily applied in practice
Design and Control of Efficient Order Picking Processes
Binnen een logistieke keten dienen producten fysiek te worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers. Tijdens dit proces worden producten gewoonlijk opgeslagen op bepaalde plaatsen (magazijnen) voor een bepaalde periode. Orderverzameling – het ophalen van producten uit de opslaglocatie in het magazijn naar aanleiding van een specifieke klantorder – is het meest kritieke magazijnproces. Het is een arbeidsintensieve operatie in handmatig bestuurde systemen, en een kapitaalintensieve operatie in geautomatiseerde systemen. Een niet optimaal functionerend orderverzamelingsproces kan leiden tot onbevredigende service en hoge operationele kosten voor het magazijn, en dientengevolge voor de hele keten. Om efficiënt te kunnen functioneren dient het orderverzamelingsproces robuust te zijn ontworpen en optimaal te worden bestuurd.
Dit proefschrift heeft als doel analytische modellen te ontwerpen die het ontwerp en de besturing van efficiënte orderverzamelingsprocessen ondersteunen. Verschillende methoden worden voorgesteld voor het schatten van de route langs de locaties van de te verzamelen producten, het bepalen van de optimale grenzen van zones in het magazijn die bestemd zijn voor opslag, de indeling van het magazijn, het aantal producten die tegelijk (in één ronde) worden verzameld (de batch size) en het aantal zones in het magazijn die worden ingericht voor het verzamelen en gereedmaken van orders. De methoden worden getest middels simulatie experimenten en worden inzichtelijk gemaakt met behulp van rekenexperimenten.Tho Le-Duc was born in 1974 in Quang Ninh, Vietnam. He received a Bachelor degree in Navigation Science from the Vietnam Maritime University in 1996 and a Postgraduate Diploma in Industrial Engineering from the Asian Institute of Technology Bangkok
Thailand (AIT) in 1998. Thanks to the financial support from the Belgian Development and Co-operations, he obtained his master degree in Industrial Management from the Catholic University of Leuven in 2000. Since May 2001, he started as a Ph.D. candidate
(AIO) at the RSM Erasmus University (formerly Rotterdam School of Management/Faculteit Bedrijfskunde), the Erasmus University Rotterdam. For about more than four years, he performed research on order picking in warehouses. As the results, Tho Le-Duc has been presented his research at several conferences in the fields of operations research,
material handling, logistics and supply chain management in both Europe and North America. His research papers have been published or accepted for publication in several refereed conference proceedings, scientific books and international journals.Within a logistics chain, products need to be physically moved from one location to another, from manufacturers to end users. During this process, commonly products are buffered or stored at certain places (warehouses) for a certain period of time. Order picking - the process of retrieving products from storage (or buffer area) in response to a specific customer request - is the most critical warehouse process. It is a labour intensive operation in manual systems and a capital intensive operation in automated systems. Order picking underperformance may lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole chain. In order to operate efficiently, the order picking process needs to be designed and optimally controlled.
Thesis Design and Control of Efficient Order Picking Processes aims at providing analytical models to support the design and control of efficient order picking processes. Various methods for estimating picking tour length, determining the optimal storage zone boundaries, layout, picking batch size and number of pick zones are presented. The methods are tested by simulation experiments and illustrated by numerical examples
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