Impact of Optimization Algorithms on Solution Efficiency: Moderating Role of Problem Complexity

Abstract

The optimization algorithms are at the heart of the process of solving complex engineering, computational and mathematical problems by enhancing the quality and efficiency of solutions. This paper will look at how optimization algorithms affect the efficiency of the solution and how the complexity of the problem can moderate this. The various optimization algorithms based on classical deterministic algorithms to the contemporary metaheuristic and evolutionary algorithms differ greatly in terms of their effectiveness to generate efficient solutions based on the degree of challenges associated with a specific problem. This paper uses conceptual analytical method to investigate the performance of the algorithms as the complexity of the problem increases. The results indicate that though higher order optimization algorithms tend to enhance the efficiency of the solution, its quality highly depends on the character and the complexity of the problem. Simple problems can be solved with simple algorithms and complex problems need adaptive and intelligent methods of optimization. The research concludes that the complexity of problems moderately affects the relationship between optimization algorithms and solution efficiency and that there should be proper selection of algorithms depending on the nature of problems.