Archive | 2019
Comparison of Dynamic Programming and Genetic Algorithm Approaches for Solving Subset Sum Problems
Abstract
Albeit Evolutionary Algorithms (EAs) are prominent, proven tools for resolution of optimization problems in the real world, appraisal of their appropriateness in solving wide variety of mathematical problems, from simple to complex, continues to be an active research area in the domain of Computer Science. This paper portrays an evaluation of the relevance of Genetic Algorithm (GA) in addressing the Subset Sum Problem (SSP) of Mathematics and providing empirical results with discussions. A GA with pertinent mutation and crossover operators is designed and implemented to solve SSP. Design of the proposed algorithm are clarified in detail. The results obtained by the proposed GA are assessed among different instances with different initial population by the intermediary solutions obtained and the execution time. This study also adapted the traditional Dynamic Programming (DP) approach, pursuing a bottom-up strategy, to solve the SSP. The findings revealed that the GA approach would be unpreferred on account of its longer execution time.