Multi-objective optimization of particle reinforced silicone rubber mould material for soft tooling process

Authors:
Arup Kumar Nandi;Shubhabrata Datta
Affiliations:
Central Mechanical Engineering Research Institute, Durgapur, WB, India;Birla Institute of Technology, Deoghar, Jharkhand, India
Venue:
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Year:
2010

Citing 4
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Abstract

Multi-objective optimizations of various conflicting objectives in designing particle reinforced silicone rubber are conducted using evolutionary algorithms to reduce the processing time of soft tooling process. A well-established evolutionary algorithm based multi-objective optimization tool, NSGA-II is adopted to find the optimal values of design parameters. From the obtained Pareto-optimal fronts, suitable multicriterion decision making techniques are used to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of soft tooling process for industrial applications.