**3. Using bat algorithm to solve MOP**

In this section, we will present the new or improved algorithm based on the characteristic of R2 or based on the influencer R2 that was used well and correctly to choose the optimal value when choosing a leader.

Bats are winged mammals and are known to be able to use echolocation. Approximately 996 unique species of bats have been identified worldwide, representing about 20% of all well-evolved mammal species [7]. Another improved computation called BAT [10] is based on the swarm concept. Using BAT, one can re-enact some echolocation features of a smaller level bat. The benefits of this approach include ease of use, versatility, and simplicity in implementation. Moreover, the approach effectively deals with a wide range of challenges, such as highly nonlinear issues. Also, BAT provides a perfect arrangement that promises quickly and works brilliantly with complex problems. Attempting to follow-up are some of the drawbacks of this estimation: conjugation occurs rapidly at first, and the rate of conjugation declines. Furthermore, no scientific study has linked factors to varying rates.

The swarm is responsible for maintaining and re-establishing the perfect Pareto arrangements that have so far been discovered, and which cannot be controlled. The most reasonable arrangement obtained is used in calculating MaBAT/R2. This approach leads people to move in order to find a solution near the best arrangement. Contrasting with Pareto's best suggestions, however, it could not be

more objective about space. The Pioneer Choice component is designed to address the research problem under study. The nondominant and most logical arrangements are recorded in a single volume. The leader selects a piece from among the stacked parts of the space layout and suggests one of the nondominant options. The random wheel is used to make the appropriate decision, along with the opportunities available to each individual: Below are full details of the proposed algorithm construction step by step based on the R2 optimum value selection component.

The performance measures in this paper are known as hypervolume (HV) [11] and inverted generational distance (IGD) [12]. Both HV and IGD are able to reflect the focus and diversity of the optimal result set of the algorithms.

Greater similarity to the original PF was indicated by a larger HV value or a smaller IGD number. For many issues, a reference point dominated by true PF is carefully selected to determine HV.

*Using Many Objective Bat Algorithms for Solving Many Objective Nonlinear Functions DOI: http://dx.doi.org/10.5772/intechopen.107078*
