劳动力
众包
调度(生产过程)
服务交付框架
计算机科学
控制(管理)
劳动力管理
劳动力规划
持续时间(音乐)
运筹学
服务(商务)
运营管理
业务
工程类
营销
经济
文学类
万维网
艺术
人工智能
经济增长
作者
Marlin W. Ulmer,Martin Savelsbergh
出处
期刊:Transportation Science
[Institute for Operations Research and the Management Sciences]
日期:2020-06-23
卷期号:54 (4): 1113-1133
被引量:63
标识
DOI:10.1287/trsc.2020.0977
摘要
Using crowdsourced delivery capacity, that is, individuals offering their vehicle and their time to perform deliveries, can allow companies to provide faster delivery options and more easily accommodate fluctuations in demand. However, because of the uncertainty associated with crowdsourced delivery capacity, ensuring service quality is more challenging. To prevent or mitigate any negative effects of the uncertainty associated with crowdsourced delivery capacity, companies may choose to also have a scheduled delivery workforce that they can control more effectively. We investigate continuous approximation and value function approximation methods for scheduling this workforce, that is, deciding their shifts (start time and duration) to achieve a service level target at minimum cost. An extensive computational study demonstrates the efficacy of our methods and provides insights into the use of crowdsourced delivery capacity.
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