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Modeling and combined application of MOEA/D and TOPSIS to optimize WEDM performances of A286 superalloy
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Multi-objective optimization of wire-electro discharge machining process by Non-Dominated Sorting Genetic Algorithm
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Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process
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Evaluation of WEDM performance characteristics of Inconel 706 for turbine disk application
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Development of highly hard and corrosion resistant A286 stainless steel through plasma nitrocarburizing process
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Microstructure and morphology of high temperature oxidation in superalloys
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Modeling and Optimization of Machining Nimonic C-263 Superalloy using Multicut Strategy in WEDM
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Experimental investigation and optimization of sustainable performance measures during wire-cut EDM of Ti-6Al-4V alloy employing preference-based TLBO algorithm
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A fast and elitist multiobjective genetic algorithm: NSGA-II
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MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
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Constrained Subproblems in a Decomposition-Based Multiobjective Evolutionary Algorithm
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MOEA/D with Adaptive Weight Adjustment
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Optimization of cutting conditions in WEDM process using regression modelling and Tabu-search algorithm
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Hybridizing the Cuckoo Search Algorithm with Different Mutation Operators for Numerical Optimization Problems
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Nickel-Based Superalloys for Advanced Turbine Engines: Chemistry, Microstructure and Properties
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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