Swarm intelligence is the study of computational systems that involves the collective cooperation of multiple agents that operate in a decentralized, self-organized, and distributed form. For instance, several optimization techniques follow this behavior, which via intelligent agents guided by high level strategies and local improvement procedures are able to efficiently solve NP-hard and NP-complete problems. During the last ten years, swarm intelligence approaches, such as ant colony optimization, particle swarm optimization, artificial bee colony, electromagnetism-like algorithm, cuckoo search, bat algorithm, firefly optimization, and black hole, have successfully been used to solve various well-known academic and real-world engineering problems in several application domains. Some examples can be mentioned such as resource planning, telecommunications, financial analysis, scheduling, space planning, energy distribution, molecular engineering, logistics, pattern classification, and manufacturing. This special issue is devoted to publish high-quality papers that employ swarm intelligence to solve complex engineering problems. Reviews on this topic are also welcome.

Potential topics include but are not limited to the following:

• Swarm intelligence algorithms for scheduling optimization
• Swarm intelligence algorithms for manufacturing optimization
• Swarm intelligence in civil engineering
• Swarm intelligence in financial engineering
• Hybrids involving swarm intelligence for engineering problems
• Integration of swarm intelligence and autonomous search for engineering problems
• Integration of swarm intelligence and big data for engineering problems
• Integration of swarm intelligence and constraint programming for engineering problems
• Parallel swarm intelligence algorithms
• Swarm intelligence using high performance computing
• Swarm intelligence frameworks for optimization