EVOLUTIONARY COMPUTATIONS

We focus on the study of evolutionary computations in developing advcanced algorithms for solving single-objective and multi-objective optimization problems with a large number of objectives and decision variables.

Evolutionary computation is an area of computer science that uses ideas from biological evolution to solve computational problems. Many such problems require searching through a huge space of possibilities for solutions. Such computational problems often require a system to be adaptive that is, to continue to perform well in a changing environment.

The automatic generation of computer programs is one of the main applications with practical relevance in the field of evolutionary computation. With program synthesis techniques not only software developers could be supported in their everyday work but even users without any programming knowledge could be empowered to automate repetitive tasks and implement their own new functionality.

Real-world optimization problems often have a large number of objectives. Hence, there is a clear requirement to develop new methods and new concepts for handling many-objective problems. Our effort is to present novel and high-performance algorithms based on evolutionary computations to tackle complex engineering problems.

Comprehensive comparative results reveal that compared with current models in the literature, our proposed evolutionary methods perform significantly more efficient. Successful results prove that our applied method can be used for variety of complex problems in space engineering and maritime industry.