Clickstream Big Data and “Delivery before Order Making” Mode for Online Retailers

Our research is inspired by a leading online retailer using clickstream big data to estimate customer demand and then ship items to customers or hubs near customers by a mode of “delivery before order making” (DBOM) mode. Using clickstream data to obtain advance demand information in order quantities, we integrate the forecasting with a singleitem uncapacitated dynamic lot sizing problem in a rolling-horizon environment. Using the simulated clickstream data, we evaluate the performance of DBOM mode

The Multi-Location Transshipment Problem with Positive Replenishment Lead Times

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

Robust Design of Public Storage Warehouses

We apply robust optimization and revenue management in public storage warehouses. We optimize the expected revenue of public storage warehouses against the worst cases with a max-min revenue objective, and the decision variables are mainly the number of storage units for each storage type. With the robust design, we can observe worst-case revenue improvement

Stochastic Modelling and Analysis of Warehouse Operations

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 differe

Sorting with Robots: where to drop off the parcel?

This paper presents a method for assigning destinations to drop off points in robotic sorting systems, taking into account robot congestion

A Real-Time Picking and Sorting System in E-Commerce Distribution Centers

Order fulfillment is the most expensive and critical operation for companies engaged in e-commerce. E-commerce distribution centers must rapidly organize the picking and sorting processes during and after the transaction has taken place, with the ongoing need to create greater responsiveness to customers. Sorting brings a relatively large setup time, which cannot be well admitted by existing polling models. We build a new stochastic polling model to describe and analyze such systems, and provide approximate explicit expressions for the complete distribution of order line waiting time for polling-based order picking systems and test their accuracy. These expressions lend themselves for operations and design operations, including deciding between “pick-and-sort” or “sort-while-pick” processes, and warehouse performance evaluation

Global Operations Strategy : Fundamentals and Practice

International audienceWhile many business schools are teaching Global Operations Strategy with self-made teaching materials, there are no such textbooks. Combining practical approaches with detailed theoretical underpinnings, this book provides theories, tools, frameworks, and techniques for global operations strategy, and brings real world perspectives to students and managers. Each chapter includes definition of key terms, introduction of fundamental theories, several short case examples, one long new case to explain the associated theories, and recommended further reading.<br/