A Decomposition-Combination Optimization Method for Network Multiobjective Optimization Problems

Abstract

In recent years, an increasing number of multiobjective evolutionary algorithms (MOEAs) have been developed for solving multiobjective optimization problems (MOPs). However, a special type of network-oriented MOPs, termed network multiobjective optimization problems (NMOPs), remains largely unexplored. In this paper, we put forth a general formulation for NMOPs, and propose the network decomposition-combination multiobjective optimization method (NDCMOM) for solving them. NDCMOM adopts a network decomposition mechanism, which breaks the NMOP down to a series of MOPs with smaller scales. The solutions to the NMOP can be obtained by combining the solutions to these smaller-scale MOPs. This decomposition-combination mechanism significantly improves the optimization efficiency. Experiments are conducted to demonstrate that the proposed NDCMOM outperforms the state-of-the-art MOEAs on large-scale NMOPs.