Sculptor Optimization Algorithm: A New Human-Inspired Metaheuristic Algorithm for Solving Optimization Problems

Abstract

In this paper, a new metaheuristic algorithm called Sculptor Optimization Algorithm (SOA) is introduced and designed, which imitates the sculpting process. The main idea in SOA design is derived from (i) making extensive changes to the sculpture material and (ii) making small and detailed changes to the sculpture. SOA theory is expressed and then mathematically modeled in two phases of exploration and exploitation. The performance of SOA in handling optimization applications has been evaluated to optimize the CEC 2017 test suite. The optimization results show that SOA, with its high power in managing exploration and exploitation during the search process, has been able to achieve suitable solutions for optimization problems. In addition, the quality of SOA results has been compared with the performance of twelve well-known metaheuristic algorithms. Analysis of the simulation results shows that SOA has provided superior performance compared to competing algorithms by achieving better results for most of the benchmark functions. Simulation findings show that compared to competing algorithms, SOA has been successful in handling 100% of unimodal functions, multimodal functions and hybrid functions, as well as 70% of composite functions.