Mega infrastructure projects are large-scale engineering facilities providing fundamental public services for social production, economic development, and people's life, such as large-scale hydropower projects, high speed railways, expressway networks, gas pipeline projects, and long-span bridges. Many mega infrastructure projects have been or are being built around the world, such as Hong Kong-Zhuhai-Macao Bridge, The Su-Tong Yangtz River bridge, High speed railway in China, and Darwin Impex LNG plant.

Traditional project management is based on three-dimensional life cycle approach where the project manager seeks to optimize the cost, quality, and design. Different from traditional construction project management, construction of mega infrastructure projects exhibits high complexity, such as task complexity, structural and directional complexity, technical complexity, and organization complexity. Due to their complexities, many of mega infrastructure projects suffered from over-budget, over-time, and low investment return. To address these challenges, many researchers have conducted extensive research on relevant topics in the recent, such as construction and site management, mega project supply chain and logistics management, risk management, and organization management.

The aim of this special issue intends to collect cutting-edge research of construction mega infrastructure projects from both academia and industry, with emphasis on current developments and future directions in new models and computational algorithms (chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory). Particularly, the original research articles to improve planning, supply chain management, and organization optimization for mega infrastructure projects are very welcome.

Potential topics include but are not limited to the following:

• Decision-making under uncertainty in project planning
• Metaheuristics algorithms (genetic algorithm, particle swarm, firefly, etc.) for large scale project planning and scheduling
• Metaheuristics algorithms for site layout optimization
• Data driven supply chain modelling
• Mega project supply chain analytics and prediction
• Risk analysis methodologies for mega project
• Uncertainty and risk management for mega project
• Simulation based stakeholder management
• Mega project organization modelling and analytics