Scheduling autonomous robots for an intralogistic application: A comparison of lookahead-based ADP strategies

作     者：Battistotti, Margherita Brandimarte, Paolo Giancola, Francesca Mazzi, Nicolo 

作者机构：Univ Manchester AMBS Booth St West Manchester M15 6PB England Politecn Torino DISMA Corso Duca Abruzzi 24 I-10129 Turin Italy Spindox Spa via Bisceglie 76 I-20152 Milan Italy Spindox Labs Srl via Cascata 56C I-38123 Trento Italy 

出 版 物：《EXPERT SYSTEMS WITH APPLICATIONS》 (Expert Sys Appl)

年 卷 期：2025年第271卷

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：European Union 

主　　题：Intralogistics Scheduling Approximate dynamic programming Rollout strategies Monte Carlo tree search 

摘      要：The increasing role of e-commerce has spurred a significant amount of research on optimization in warehousing management, including routing and scheduling issues. When material handling is rigidly automated, a deterministic scheduling problem arises, for which solution strategies have been proposed in the literature. A recent trend is the introduction of autonomous robots, which may interact with human operators and offer additional flexibility in item manipulation. The resulting problem is affected by uncertainty, due to the interaction between robots and human workers and the possible failure in items manipulation. In the paper, we propose an adaptation of approximate dynamic programming strategies with limited lookahead, namely, rollout strategies and Monte Carlo tree search. The idea can be interpreted as an intermediate approach between the solution of a deterministic problem, disregarding uncertainty and using a long lookahead, or the application of pure state-based dispatching rules with no lookahead. The proposed approaches are compared against exact dynamic programming on small-size instances, and then evaluated on larger instances, proving their viability.