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Centre for Smart Warehousing and Logistics Systems research themes

We produce business-focused research to solve logistical problems, with an emphasis on the use of technology.


Warehousing and material handling

  • We investigate the efficiency and effectiveness of warehouse operations along with the role of warehouses in supply networks and distribution systems.
  • We develop optimisation tools and decision support systems for warehouse operations (such as order picking) and facility planning.
  • We study the role of technology and automation (e.g. robotics, augmented reality) in designing and managing warehouses.

Transport and distribution

  • We look at the challenges associated with the movement of freight and people.
  • We investigate the movement of products in distribution networks.
  • We also look at the movement of people across airline operations and networks, cycling and bike sharing and public bus services.

E-commerce logistics

  • We investigate how the digital economy has created new challenges for logistics operations, along with systems that satisfy these requirements.

Our approach

The overarching research question associated with the Centre considers the meaning and role of smart and digital approaches in warehousing and logistics. To examine this question, we focus not only on studying this area but also on developing practical tools and systems. In order to do so, we utilise different methods and tools that fall into the following categories.

Digital and automation technologies

  • The emergence of affordable and well-integrated information and communication technologies has created opportunities for their adoption by logistics firms.
  • We investigate how different digital and automation technologies affect current operations and decision-making processes and we evaluate their impact to potential users.
  • This is often done utilising mathematical and engineering tools, but we also utilise more qualitative techniques to examine this emerging paradigm, considering issues of technology adoption and assimilation for example.

Data analytics

  • This includes the collection and processing of operational datasets for problem identification and for prediction of future circumstance and problems.
  • Data analytics techniques coupled with optimisation and simulation tools can lead to prescriptive tools that support decision making.

Modelling, optimisation and simulation

  • The complex and inter-related nature of the decisions around warehousing and logistics calls for the formulation of quantitative models and development of solution approaches to understand the relationships between these decisions, observe their effects on the overall performance of the operations, and propose “optimal” or “near-optimal” decisions that aim to maximise their efficiency and effectiveness.


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