Dynamic Incentive Mechanism for Delivery Slot Management in E-Commerce Attended Home Delivery

2020 ◽  
Vol 54 (3) ◽  
pp. 567-587 ◽  
Author(s):  
Albert Vinsensius ◽  
Yuan Wang ◽  
Ek Peng Chew ◽  
Loo Hay Lee

In attended home delivery, challenges arise in practice because of the short strict time windows, stochastic customer requests, and varying customers’ preferences for delivery slots. In this study, we focus on integrating dynamic time slot incentives and order delivery with the intention of reducing overall delivery cost and improving profitability. The proposed incentive mechanism is able to exploit the variability in the marginal fulfillment cost of an order and the customers’ preferences to influence the customers’ selection of delivery slots. We present an approximate dynamic programming approach to estimate the marginal fulfillment cost using the operational vehicle routing cost while accounting for future orders. We demonstrate that the proposed incentive mechanism can achieve a high level of savings (of up to 70%) with respect to the benchmark customer-free-choice scenario. It is also noted that the proposed mechanism effectively exploits higher order density and vehicle availability to achieve a higher level of savings.

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ciril Bohak ◽  
Matija Marolt

The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.


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