Performance Evaluation of Anti-Predatory Nature-Inspired Algorithm on the CEC'14 Test Suites
Rohit Kumar Sachan, Shrabani Mallick · 2023
Anti-Predatory Nature-Inspired Algorithm (APNIA) is a recent proposal in evolutionary computations. It emulates the self-preservation strategies of frogs. It has several advantages, like a reasonable convergence rate, a balance between exploration and exploitation, and preserving diversity in solutions during the evolution process. Apart from different types of evaluations, CEC benchmarking problems are one of the finest test suites that measure the performance of an evolutionary algorithm. With this motive, this work evaluates the performance of the APNIA in solving CEC'14 benchmarking problems. We evaluate the performance of APNIA based on the CEC'14 guidelines. Our experimental evaluations demonstrate the moderated performance of APNIA for solving the CEC'14 test suite problems in different dimensions.