With the availability of big data and the improvement of computing power, optimisation theory and algorithms are increasingly attractive in economics and business. The combination of big data, optimisation theory and algorithms can help us better understand the evolutionary behaviour of complex systems, provide us new insights into the complexity of economics and business, and help us better evaluate, monitor and predict economic and business systems.

For real-life optimisation problems in economics and business, we must consider many traditional factors, such as quality, quantity, cost, time, profit, productivity, sustainability, reliability, safety, innovation, and social responsibility. Meanwhile, we also must consider various new developments of technology, such as social networks, Internet of things (IoT), artificial intelligence (AI), share economics, blockchain, and industry 4.0. These new developments are new challenges as well as opportunities to researchers specialising in complexity in optimisation theory and algorithms.

The aim of this Special Issue is to collate original research on the complexity of optimisation theory and algorithms, focusing on integrating conceptual methodologies of the optimisation domain with empirical issues in economics, business etc. This Special Issue hopes to gather new insights, models, algorithms, and their applications in a wide range of topics. Submissions that debate on frontiers and complexity in optimisation theory and algorithms are particularly encouraged. Review articles discussing the state of the art are also welcome.

Potential topics include but are not limited to the following:

• Frontiers in optimisation theory within IoT
• Frontiers in optimisation theory within AI
• Frontiers in optimisation theory within blockchain technologies
• Frontiers in optimisation theory within share economics
• Complexity of algorithms for advanced optimisation problems
• Robust optimisation for decision problems with uncertainty
• Optimisation problems with imprecise data
• Manufacturing system design and optimisation
• Complexity of optimisation in supply chain
• Complexity of dynamic game theory and its applications
• Complexity of optimisation in data-driven models