The recent release and public engagement with generative AI and ChatGPT in particular has provided a pertinent reminder of how rapidly the capabilities of AI based solutions are improving. ChatGPT has proven to be quite disruptive in creative fields, or indeed any field that heavily relies on (previously human) written communication, but when it comes to the Supply Chain, many of its more difficult problems are not suitable for generative AI and a different approach is needed. Luckily AI is a diverse discipline with a wide range of tools, able to perform tasks that typically require human intelligence some of which are very much applicable to supply chain problems. Computational Intelligence (CI) is one of those tools – a subset of AI that specializes in problem-solving techniques inspired by nature and biology. It encompasses a range of methods, including evolutionary algorithms, fuzzy logic, neural networks, and swarm intelligence. These approaches are particularly well-suited for solving complex, dynamic, and uncertain problems—characteristics often encountered in supply chain management.
Supply chain management is fraught with various challenges that make it an ideal candidate for CI-based solutions:
Computational Intelligence can be applied to each of these very real challenges faced by any organisation reliant on logistics and supply chain processes and while still in the early stages of its supply chain journey it has potential to make a real impact for the better
While general AI has made significant strides in improving supply chain management, there are scenarios where Computational Intelligence shines even brighter. Its ability to handle uncertainty, multi-objective optimization, and complex, dynamic systems positions CI as a valuable tool for addressing the unique challenges of supply chain management. By embracing CI techniques, businesses can enhance their supply chain’s efficiency, resilience, and adaptability, ultimately gaining a competitive edge in today’s dynamic marketplace.
This evolution is just starting to have an impact on the real-life processes and challenges faced by many of those needing to improve and optimise their warehouse operation. Orquestr8 by Breathe Technologies is an AI based software platform that problems solves and optimises warehouse processes using the abilities of CI to simplify the integration of core warehouse functions and provide a harmonised eco system. It’s pick optimisation module is a great example of CI handling the interconnected processes and multiple objectives of the pick operation and making smart decisions to work out the optimal batching and route navigation that can reduce the pick walking distance by up to 50%.
Our recent picking article provides more insight into Pick Optimisation and key considerations when assessing opportunities to improve productivity, efficiency and accuracy.
As supply chains continue to evolve, the integration of Computational Intelligence is likely to continue to play a pivotal role in shaping their future success.