Discussing the article: "Blood inheritance optimization (BIO)"

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Check out the new article: Blood inheritance optimization (BIO).

I present to you my new population optimization algorithm - Blood Inheritance Optimization (BIO), inspired by the human blood group inheritance system. In this algorithm, each solution has its own "blood type" that determines the way it evolves. Just as in nature where a child's blood type is inherited according to specific rules, in BIO new solutions acquire their characteristics through a system of inheritance and mutations.

Each of us carries in our veins a unique combination inherited from our parents. Just as blood types determine compatibility during transfusions, they could determine how parameters are transferred and mutated during the optimization. I liked this idea and decided to come back to it when I had time to do research. After conducting experiments, the Blood Inheritance Optimization (BIO) algorithm was born – a method that uses the natural laws of blood group inheritance as a metaphor for managing the evolution of decisions. In the algorithm, the four blood types evolved into four different strategies for mutation of parameters, and the laws of inheritance determined how offspring acquire and modify the characteristics of their parents.

As in nature, a child's blood type is not a simple average of the parents' blood types, but is subject to genetic laws. In BIO, the parameters of new solutions are formed through a system of inheritance and mutations. Each blood type brings its own unique approach to exploring the solution space: from conservatively preserving the best values found, to radical mutations that open up new promising areas and directions for further research into the solution space.

In this article, I would like to share the principles of the BIO algorithm, which combines biological inspiration with algorithmic rigor, and provide test results on functions we are already familiar with. So, let us do that.

Author: Andrey Dik