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A combination weighting model based on iMOEA/D-DE

https://doi.org/10.1631/fitee.2000545

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What this work says

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A fast and elitist multiobjective genetic algorithm: NSGA-II

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Self-Adaptive Differential Evolution Algorithm With Zoning Evolution of Control Parameters and Adaptive Mutation Strategies

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MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition

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Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II

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Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front

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IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems

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A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization

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An Evaluating Method with Combined Assigning-Weight Based on Maximizing Variance

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GRA-TOPSIS emitter threat assessment method based on game theory

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Allocation Model of Carbon Emission Permits for the Electric Power Industry with a Combination Subjective and Objective Weighting Approach

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An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

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Comprehensive Evaluation of the Sustainable Development of Power Grid Enterprises Based on the Model of Fuzzy Group Ideal Point Method and Combination Weighting Method with Improved Group Order Relation Method and Entropy Weight Method

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Surface Water Quality Evaluation Based on a Game Theory-Based Cloud Model

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Constrained Optimization Evolutionary Algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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