Genetic optimization algorithms applied toward mission computability models
This work addresses computational problems in mission-critical domains, but it appears incremental as it applies existing genetic algorithms without clear new breakthroughs.
The paper tackled a mission-critical and constraints-aware computation problem by applying genetic optimization algorithms, resulting in a feasible solution as described.
Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are heuristics based and low cost to compute. Genetic algorithms use selection, crossover, and mutation to obtain a feasible solution to computational problems. In this paper, we describe our genetic optimization algorithms to a mission-critical and constraints-aware computation problem.