http://repub.eur.nl/res/aut/8337/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/37198/ 2011-10-01T00:00:00Z This paper provides an overview of stochastic research in warehouse operations. We identify uncertainty sources of warehousing systems and systematically present typical warehouse operations from a stochastic system viewpoint. Stochastic modeling methods and analysis techniques in existing literature are summarized, along with current research limitations. Through a comparison between potential and existing stochastic warehouse applications, we identify potential new research applications. Furthermore, by comparing potential and existing solution methods, methodological directions relevant to practice and largely unexplored in warehouse literature are identified. http://repub.eur.nl/res/pub/22200/ 2010-02-01T00:00:00Z This paper develops a novel framework to evaluate the integral performance of order picking systems with different combinations of storage and order picking policies. The warehousing literature on order picking mostly considers minimizing either elapsed time or distance as the sole objective, whereas warehouse managers in a supply chain have to look beyond single-dimensional performance and consider trade-offs among different criteria. Thus managers still need a unified and efficient framework to select a portfolio of appropriate order picking policies from a multi-criteria and contextual perspective. Our framework—combining data envelopment analysis, ranking and selection, and multiple comparisons—provides an efficient methodology to simultaneously analyze several interrelated problems in order picking systems with multiple performance attributes, such as service levels and operational costs. We demonstrate our approach through comprehensive evaluations of order picking policies in three low-level, picker-to-parts rectangular warehouses facing demand variations. http://repub.eur.nl/res/pub/19574/ 2010-01-01T00:00:00Z This paper develops a novel framework to evaluate the integral performance of order picking systems with different combinations of storage and order picking policies. The warehousing literature on order picking mostly considers minimizing either elapsed time or distance as the sole objective, whereas warehouse managers in a supply chain have to look beyond single-dimensional performance and consider trade-offs among different criteria. Thus managers still need a unified and efficient framework to select a portfolio of appropriate order picking policies from a multi-criteria and contextual perspective. Our framework-combining data envelopment analysis, ranking and selection, and multiple comparisons-provides an efficient methodology to simultaneously analyze several interrelated problems in order picking systems with multiple performance attributes, such as service levels and operational costs. We demonstrate our approach through comprehensive evaluations of order picking policies in three low-level, picker-to-parts rectangular warehouses facing demand variations. http://repub.eur.nl/res/pub/16724/ 2009-09-03T00:00:00Z This thesis has studied stochastic models and analysis of warehouse operations. After an overview of stochastic research in warehouse operations, we explore the following topics. Firstly, we search optimal batch sizes in a parallel-aisle warehouse with online order arrivals. We employ a sample path optimization and perturbation analysis algorithm to search the optimal batch size for a warehousing service provider, and a central finite difference algorithm to search the optimal batch sizes from the perspectives of customers and total systems. Secondly, we research a polling-based dynamic order picking system for online retailers. We build models to describe and analyze such systems via stochastic polling theory, find closed-form expressions for the order line waiting times, and apply polling-based picking to online retailers. We then present closed-form analytic expressions for pick rates of order picking bucket brigades systems in different storage profiles, and show how to combine storage policies and bucket brigades protocols to improve order picking productivity. Finally, we propose a new warehouse design approach oriented to improving revenue management of public storage warehouses. Our experiments show a proper facility design can significantly improve the expected revenue of public storage warehouses. http://repub.eur.nl/res/pub/15149/ 2008-09-11T00:00:00Z One of the challenging questions that online retailers are currently facing is how to organize the logistic fulfillment processes both during and after a transaction has taken place. As new information technologies become available that allow picking information to be conveyed in real time and with the ongoing need to create greater responsiveness to customers, there is increasing interest in applying dynamic picking in the warehouses of online retailers. In a Dynamic Picking System (DPS), a worker picks orders that arrive in real time during the picking operations and the picking information can dynamically change in a picking cycle. Models to describe and analyze such systems via stochastic polling theory are presented and closed-form expressions for the order line waiting times in a DPS are derived. These analytical results are verified by simulation. It is shown that the application of polling-based picking can generally lead to shorter order throughput times and higher on-time service completion ratios than traditional batch picking systems using optimal batch sizes. It is demonstrated that the proposed analysis method can be applied to minimize warehouse cost and improve service. http://repub.eur.nl/res/pub/7947/ 2006-09-07T00:00:00Z Transshipments, monitored movements of material at the same echelon of a supply chain, represent an effective pooling mechanism. With a single exception, research on transshipments overlooks replenishment lead times. The only approach for two-location inventory systems with non-negligible lead times could not be generalized to a multi-location setting, and the proposed heuristic method cannot guarantee to provide optimal solutions. This paper uses simulation optimization by combining an LP/network flow formulation with infinitesimal perturbation analysis to examine the multi-location transshipment problem with positive replenishment lead times, and demonstrates the computation of the optimal base stock quantities through sample path optimization. From a methodological perspective, this paper deploys an elegant duality-based gradient computation method to improve computational efficiency. In test problems, our algorithm was also able to achieve better objective values than an existing algorithm.