CIPLS 2017 - 2017 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS'17)

The management of production and logistics systems in today's fierce competition environment is a difficult task and has become progressively complex. Major changes in products, processes, technologies, and societies bring along remarkable challenges and increasing market demands. Modelling and optimisation of complex problems arising in production and logistics systems is of paramount importance in surviving and achieving competitive gain in productivity and quality.
In recent years, the advancements in computer technology have allowed researchers to tackle large-scale problems and to develop and integrate efficient optimisation techniques for solving them. Within this context, CIPLS aims to address issues related to the design, planning, control, and continuous improvement of production and logistics systems using computational intelligence, including local search methods, evolutionary algorithms and other nature-inspired optimisation techniques. Nevertheless, we also welcome submissions describing innovative operations research and/or decomposition methods that are able to provide state-of-the-art solutions to the aforementioned issues, as a way to encourage interactions between researchers from computational intelligence and the general operations research community. The intention is to cover various aspects of production from aggregate planning to shop-floor execution systems and modelling, planning and control of logistics systems. Studies incorporating real-world applications are highly encouraged.
Topics
Recommended topics include, but are not limited to, the following:
Production planning and control
Flexible manufacturing systems
Integrated production system and process design
Capacity planning
Lot sizing
Assembly lines
Inventory control
Facilities planning and design
Transport and distribution planning
Vehicle routing and scheduling
Multi-modal transport
Sustainability and green logistics
Logistics network design
Decision support systems in production and logistics