Development of a Multi‐objective Salp Swarm Algorithm for Benchmark Functions and Real‐world Problems
Sushant P. Mhatugade, Ganesh M. Kakandikar, Omkar K. Kulkarni, Vilas M. Nandedkar · 2019
The salp swarm algorithm (SSA) and the multi-target salp swarm algorithm (MSSA) have made progress towards various benchmark test capacities to aid and demonstrate the execution of the algorithm. This chapter aims to assess the SSA and MSSA and compare them with actual outcomes. It analyzes the SSA for various test functions and problems. In these types of problems, the arrangement must fulfill a few conditions known as constraints. The types of constraints are: equality constraints, inequality constraints and whole number constraints. The set that fulfills all constraints in the issue is known as the feasible set. Constrained and unconstrained optimization test functions were used to validate the results obtained from the SSA and MSSA. Furthermore, the MSSA was used for the validation of the results of a real-world application, i.e. a cantilever beam. The MSSA offers competitive solutions compared with the other multi-objective algorithms and it offers a wider range of non-dominated solutions.