IMMUNE NETWORK SIMULATION WITH MULTIOBJECTIVE GENETIC ALGORITHMS FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION |
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Authors: | A. KURAPATI S. AZARM |
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Affiliation: | Department of Mechanical Engineering , University of Maryland , College Park, Maryland, 20742, USA |
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Abstract: | The paper presents a method called MOGA-INS for Multidisciplinary Design Optimization (MDO) of systems that involve multiple competing objectives with a mix of continuous and discrete variables. The method is based on the Immune Network Simulation ( INS) approach that has been extended by combining it with a Multi-Objective Genetic Algorithm ( MOGA). MOGA obtains Pareto solutions for multiple objective optimization problems in an all-at-once manner. INS provides a coordination strategy for subsystems in MDO to interact and is naturally suited for genetic algorithm-based optimization methods. The MOGA-INS method is demonstrated with a speed-reducer example, formulated as a two-level two-objective design optimization problem. |
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Keywords: | Balancing Imbalance compensation Hard disks Vibration control |
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