An Approach of Constructing Multi-Objective Pareto Optimal Solutions Using Arena’s Principle
Jin Yan Zheng · 2007
This paper proposes an approach, namely the arena’s principle (AP), to construct the Pareto optimal solutions by utilizing features of the multi-objective evolution. It is proved that the AP works correctly and its computational complexity is O(rmN) (0m/N1). Theoretically, when AP is compared with Deb’s algorithm and Jensen’s algorithm (their computational complexity are O(rN2) and O(Nlog(r?1)N) respectively), AP is better than Deb’s, and is also better than Jensen’s when the objective number r is relatively large (such as r≥5). Moreover, AP performs better than the other two algorithms when m/N is relatively small (such as m/N≤50%). Experimental results indicate that AP performs better than the other two algorithms on the CPU time efficiency. In applications, AP can be integrated into any Pareto-based MOEA to improve its running efficiency.