Amazon Locker Capacity Management
Amazon Locker is a self-service delivery or pickup location where customers can pick up packages and drop off returns. A basic first-come-first-served policy for accepting package delivery requests to lockers results in lockers becoming full with standard shipping speed (3-5 day shipping) packages, and leaving no space left for expedited packages which are mostly Next-Day or Two-Day shipping. This paper proposes a solution to the problem of determining how much locker capacity to reserve for different ship-option packages. Yield management is a much researched field with popular applications in the airline, car rental, and hotel industries. However, Amazon Locker poses a unique challenge in this field since the number of days a package will wait in a locker (package dwell time) is, in general, unknown. The proposed solution combines machine learning techniques to predict locker demand and package dwell time, and linear programming to maximize throughput in lockers. The decision variables from this optimization provide optimal capacity reservation values for different ship options. This resulted in a year-over-year increase of 9% in Locker throughput worldwide during holiday season of 2018, impacting millions of customers.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Dynamic Demand Management for Parcel Lockers
In pursuit of a more sustainable and cost-efficient last mile, parcel lockers have gained a firm foothold in the parcel delivery landscape. To fully exploit their potential and simultaneously ensure customer satisfaction…
ManagementCooperative Sensing of Side Lobes Interference for mmWave Blockages Localization and Mapping
Radio localization and sensing are anticipated to play a crucial role in enhancing radio resource management in future networks. In this work, we focus on millimeter-wave communications, which are highly vulnerable to bl…
ManagementPositionNeural Coordination and Capacity Control for Inventory Management
This paper addresses the capacitated periodic review inventory control problem, focusing on a retailer managing multiple products with limited shared resources, such as storage or inbound labor at a facility. Specificall…
Deep Reinforcement LearningManagementLocker-based Truck-Drone Routing with Integrated Considerations of Pickups, Deliveries, and No-Fly Zones
Truck-drone delivery is an emerging last-mile logistics mode combining the long-haul capacity of trucks with the flexible service capability of drones. In locker-based operations, smart lockers serve not only as temporar…
Reinforcement LearningSensing of Side Lobes Interference for Blockage Prediction in Dense mmWave Networks
The integration of sensing capability in the design of wireless communication systems is foreseen as a key enabler for efficient radio resource management in next-generation networks. This paper focuses on millimeter-wav…
Management