**5.2 Challenges**

Bio-inspired algorithms face challenges in design of competitive and interactive component design. Biological systems have found lack in information exchange so algorithm has to be developed in absence of data. Improve or develop bio-inspired algorithms to design solution to adapt for any real-world problem. Performance of bioinspired algorithm is another issue which need to be sorted in working environment.

**Figure 13.** *List of publications on different bio-optimization.*

**Figure 14.** *Frequency of research articles published on various based algorithms till 2021 bio-inspired algorithms year wise.*

#### **5.3 Future scope**

Bio-inspired algorithms brought revolutionary changes in different domains as well got power to impact further generation computing. The application coverage area is vast compared conventional methods includes modeling, algorithm, engineering and computing. Generally, optimization techniques based on swarm search procedures incorporate random changes and identification and still has capacity grow which is attracting many young researchers. Bio-inspired algorithms still require addressing new technologies along with it by exploring new ways to adopt algorithms. In order to achieve they need to be collaborated with research communities like computer science, biology, artificial intelligence, ecology, quantum and others. Currently, many bio-inspired algorithms exist, and application field is also extensive and obviously work require further exploration,

