- To propose a new algorithm that offers a different solution pattern to the optimization problem
- To improve the drawbacks of the existing metaheuristics in local and global search
- To enhance the searching capabilities of the hybrid algorithm by bringing the powerful features of the different algorithms into the one.
CURRENT STATE OF THE RESEARCH
- A new distribution based metaheuristic called Elitist Stepped Distribution Algorithm (ESDA)* is proposed by inspiring the drawbacks in the searching capabilities of Cross Entropy Method (CEM). The proposed algorithm presents a solution pattern covering the solution approach of both CEM and Big Bang Big Crunch. It generates competitive results for unconstrained test problems and constrained engineering problems.
- The exploration capability of Cuckoo Search and Flower Pollination algorithms are enhanced by replacing their Levy fligth based solution update procedure with mutation and crossover operators of Differential Evolutions. The analysis results in both papers** shows that the hybrid algorithm improves the results of both CS/FPA and DE, and generates robust solution for the engineering problems.