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DIP-MOEA:a double-grid interactive preference based multi-ob jective evolutionary algorithm for formalizing preferences of decision makers

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Frontiers of Information Technology & Electronic Engineering 2022年第11期23卷 1714-1732页

作者： Luda ZHAO Bin WANG Xiaoping JIANG Yicheng LU Yihua HU College of Electronic Engineering National University of Defense TechnologyHefei 230037China Third Interdisciplinary Center National University of Defense TechnologyHefei 230037China Unit 78092 of People's Liberation Army of China Chengdu 610000China

The final solution set given by almost all existing preference-based multi-objective evolutionary algorithms(MOEAs)lies a certain distance away from the decision makers’preference information ***,we propose a multi-ob jective optimization algorithm,referred to as the double-grid interactive preference based MOEA(DIPMOEA),which explicitly takes the preferences of decision makers(DMs)into ***,according to the optimization ob jective of the practical multi-ob jective optimization problems and the preferences of DMs,the membership functions are mapped to generate a decision preference grid and a preference error ***,we put forward two dominant modes of population,preference degree dominance and preference error dominance,and use this advantageous scheme to update the population in these two ***,the populations in these two grids are combined with the DMs’preference interaction information,and the preference multi-ob jective optimization interaction is *** verify the performance of DIP-MOEA,we test it on two kinds of problems,i.e.,the basic DTLZ series functions and the multi-ob jective knapsack problems,and compare it with several different popular preference-based *** results show that DIP-MOEA expresses the preference information of DMs well and provides a solution set that meets the preferences of DMs,quickly provides the test results,and has better performance in the distribution of the Pareto front solution set.

关键词： Multi-objective evolutionary algorithm(MOEA) Formalizing preference of decision makers population renewal strategy Preference interaction

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