Advancement in the twentieth century in artificial immune systems for optimization: Review and future outlook

Research in Artificial Immune Systems (AIS) for optimization has attracted attention in recent years. Exploration and adoption of the inspired immune theories in clonal selection, immune network, negative selection, and danger signaling is becoming a popular basis for algorithm design for solving optimization problems, especially on multi-objective optimizations. Novel algorithms are design, benchmarked and applied to real life applications. This paper aims to review and outlook on the latest development of AIS-based algorithms in the recent decade. An analysis of the AIS applications is also discussed.