A sustainable city is a city designed with consideration for social, economic, and environmental impact, as well as a resilient habitat for existing populations, without compromising the ability of future generations to experience the same. These cities are inhabited by people who are dedicated towards minimization of the required inputs of energy, water, and food, and the output of heat, waste, air pollution (such as CO2 and methane) and water pollution.

However, the connectivity between citizens, systems, and things in cities creates tremendous complexity when it comes to decision-making, and this connectivity is always reflected in many engineering issues, such as cleaner energy systems, low-carbon transportation, and green industry, etc. Therefore, the topic of sustainable cities has already attracted a lot of attention from engineers and applied mathematicians. The recent advances in modeling methods based on mathematical programming, data mining, machine learning, and statistical inference create a new paradigm for the management of sustainable cities.

This Special Issue aims to collate original research and review articles with a focus on addressing the challenges associated with sustainable cities. We welcome submissions with a focus on interdisciplinary modeling methods for intelligently and efficiently solving certain sustainability-related issues and those aimed at bringing the attention of the academic and industrial community to how emerging methodological techniques fill the current gap in knowledge.

Potential topics include but are not limited to the following:

• Mathematical programming for sustainable city applications
• Data mining and machine learning for sustainable city applications
• Decision support systems for sustainable city applications
• Modelling for urban infrastructure design and planning
• Urban mobility modelling in the sustainable city paradigm
• Cleaner energy system integration in the sustainable city paradigm
• Interdependencies of sustainable cities and information technology
• Interdisciplinary modeling methods for urban pollution control
• Interdisciplinary modeling methods for sustainable policy analysis