In this paper, we propose an interactive method for DMEA-II and apply it to a spam-email detection system. In DMEA-II, an explicit niching operator is used with a set of rays which divides the space evenly for the selection of nondominated solutions to fill the solution archive and the population of the next generation. | VNU Journal of Science: Comp. Science & Com. Eng. Vol. 30, No. 4 (2014) 29–43 Toward an Interactive Method for DMEA-II and Application to the Spam-Email Detection System Long Nguyen1 , Lam Thu Bui1 , Anh Quang Tran2 1 Le Quy Don Technical University, Vietnam 2 Hanoi University, Vietnam Abstract Multi-Objective Evolutionary Algorithms (MOEAs) have shown a great potential in dealing with many real-world optimization problems. There has been a popular trend in getting suitable solutions and increasing the convergence of MOEAs by consideration of Decision Makers (DMs) during the optimization process (in other words interacting with DM). Activities of DM includes checking, analyzing the results and giving the preference. In this paper, we propose an interactive method for DMEA-II and apply it to a spam-email detection system. In DMEA-II, an explicit niching operator is used with a set of rays which divides the space evenly for the selection of nondominated solutions to fill the solution archive and the population of the next generation. We found that, with DMEA-II solutions will effectively converge to Pareto optimal sets under the guidance of the ray system. By this reason, we propose an interactive method using three Ray based approaches: 1) Rays Replacement: The furthest rays from DM’s preferred region are replaced by new rays that generated from set of reference points. 2) Rays Redistribution: Which redistribute the system of rays to be in DM’s preferred region. 3) Value Added Niching: Based on the distances from non-dominated solutions in archive to DM’s preferred region, the niching values for the solutions is increased to be priority selected. By those approaches for the proposal interactive method, the next generation will be guided toward the DM’s preferred region. We carried out a case study on several popular test problems and it obtained good results. We apply the proposed method for a real application in a spam-email detection system. With this system, a
