Introduction to the Special Theme
by Rob van der Mei, CWI, and Ariona Shashaj, SICS
In December 2013, one of the biggest online retailers announced its intention to use drones to deliver products to consumers. Perhaps the next step towards future logistics will be the use of teleportation beams! Although we are under no immediate threat of being pelted by delivery drone rain while dodging teleporting beams of products, logistics systems have undoubtedly become more complex in order to face new challenges imposed by the growth of the global market, mass urbanization, and the move towards sustainability. This Special Theme of the ERCIM News is dedicated to recent advancements in logistics, planning, scheduling and supply chain optimization.
Logistics is the science that orchestrates the flow of resources through supply chains in terms of transportation mode, warehousing and third-party organization. Modern logistics and service systems need to provide efficiency, correctness and robustness in the process of planning and controlling the raw materials, products and people flows and the related information. Some current challenges within logistics include: the globally dispersed nature of companies; the increase in diversity of storage and transportation modes; the mass urbanization that has occurred over the last decade; and the requirements for flexibility, transparency and sustainability.
These challenges notwithstanding, the recent advances in ICT technologies make it possible to have the right resources in the right place at the right time. There is a growing interest and increased research efforts in data science and big data, which are set to become powerful tools for future logistics. The development of machine-learning and data-mining algorithms and their application to complex and voluminous data in order to extract knowledge will improve logistics operations and supply chain management systems by achieving transparency and control over entire systems, improving predictive analysis and risk assessment as well as real-time adjustment and responses to environmental conditions.
By enriching the physical world with contextual information, Augmented Reality (AR) is an emergent technology which will play a fundamental role in the future of industrial processes. The benefits of AR applications in the fields of logistics and planning operations range from sensory integrative models to intelligent transportation and execution of maintenance/warehouse operations.
A selection of articles in this special theme discusses the potential use of these cutting-edge technologies to logistics operations, such as data-drive models derived through big data techniques and the potential use of machine-learning approaches for intelligent transportation systems, as well as remote maintenance systems through AR applications.
Although the improvement of emerging technologies will lead us to the future of logistics, what stands behind today’s efficient logistics operations and planning is the application of mathematical tools. This special theme includes a selection of publications that provide an overview of these tools and their application. In particular, an open source optimization framework is discussed and used within specific case studies in logistics, such as risk assessment and vehicle route optimization. Stochastic optimization is discussed in two different contexts: firstly, in solving placement and packing problems in scenarios involving complex industrial objects, and secondly to efficiently plan complex supply network and logistics maintenance operations. Mixed integer programming techniques are used to optimize train timetables and reduce losses on railway infrastructure capacities while satisfying time constraints and quality of service.
A selection of four articles describe the simulation models and test beds in the field of logistics and planning operations: application of simulation-based optimization approach in order to improve the distribution network of grocery retail stores, description of a 3D modelling software for production factory planning, development of a test bed infrastructure for logistics and transportation, and the study of new models towards global collaborative and robust production networks.
Finally, some real world case studies are included in this special theme: modelling and validation of a system for shipping lane management; study of the impact of patient logistics management on breast cancer treatment; improving the planning and distribution of fire-fighter stations and vehicles; study of the challenges related to the cash supply chain network; and optimizing the planning of railway shunting yards.
Rob van der Mei, CWI
Ariona Shashaj, SICS