Parallel Approaches in MOACOs for Solving the Bi-criteria TSP: A Preliminary Study

This work presents two parallelization schemes applied to three different Multi-Objective Ant Colony Optimization (MOACO) algorithms. The aim is to get a better performance, improving the quality, quantity and the spread of solutions over the Pareto Front (the ideal set of solutions), rather than just reduce the running time. Colony-level (coarse-grained) implementations have been tested for solving two instances of the Bi-criteria TSP problem, yielding better sets of solutions, in the mentioned sense, than the correspondent sequential approach.

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