A NEW METAHEURISTIC BASED ON DETERMINISTIC FINITE AUTOMATON FOR MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS

In this paper we state a novel metaheuristic based on Deterministic Finite Automaton (DFA) for the multi-objective optimization of combinatorial problems. First, we propose a new DFA based on Swapping (DFAS). DFAS allows the representation of feasible solutions space of combinatorial problems. Last, we define an algorithm that works with DFAS, it is named Exchange Deterministic Algorithm (EDA). EDA has three steps. The first step consists in create the initial solutions, the second step improves the initial solutions and the last step uses transitions between the states of the DFAS for improving the solutions. EDA was tested using well known instances of the Bi-objective Traveling Salesman Problem (TSP). EDA results were compared against Exhaustive Techniques from the specialized literature using Multiobjective Metrics. The results shows that EDA solutions are close to the Optimal Solutions.