Investigation of the impact of different versions of GCC on various metaheuristic-based solvers for traveling salesman problem

A compiler is a system software that takes code written in a high-level language as input and converts it into machine code by selecting the appropriate instructions from the instruction set of the corresponding computer architecture. Thus, depending on this selection process, different conversions with the same functionality are possible. Consequently, there are studies in the literature that compare the performance of different compilers on problems from various domains. However, to the best of our knowledge, no research has yet investigated the impact of different versions of a compiler on the optimization domain. This study seeks to fill this research gap by examining the effects of different versions of GCC on TSP, a well-known combinatorial optimization problem, for the first time in the literature. In this respect, seven different versions of GCC were employed, and four widely used metaheuristics, namely Simulated Annealing, Genetic Algorithm, Tabu Search, and Ant Colony Optimization, were implemented in C++ programming language to solve TSP. The experiments conducted have revealed that different versions of GCC make a significant difference in the performance of various metaheuristic-based solvers for TSP.