%0 Journal Article
	%A Vincenzo Capalbo and  Gianpaolo Ghiani and  Emanuele Manni
	%D 2021
	%J International Journal of Economics and Management Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 171, 2021
	%T The Role of Optimization and Machine Learning in e-Commerce Logistics in 2030
	%U https://publications.waset.org/pdf/10011929
	%V 171
	%X Global e-commerce sales have reached unprecedented
levels in the past few years. As this trend is only predicted to
go up as we continue into the ’20s, new challenges will be faced
by companies when planning and controlling e-commerce logistics.
In this paper, we survey the related literature on Optimization and
Machine Learning as well as on combined methodologies. We
also identify the distinctive features of next-generation planning
algorithms - namely scalability, model-and-run features and learning
capabilities - that will be fundamental to cope with the scale and
complexity of logistics in the next decade.
	%P 294 - 298