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Bilevel multiobjective packaging optimization for automotive design
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DOI：10.1007/s00158-014-1120-0.png)
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The successful application of multiobjective optimization to engineering problems has motivated studies of more complex systems involving multiple subsystems and design disciplines, each with multiple design criteria. Complex system design requires participation of different teams that are highly specialized within each discipline and subsystem. Such a high differentiation results in limited sharing of information among the design teams. The mathematical modeling and the solution algorithm proposed in this paper address the issue of coordinating multiple design problems that negotiate according to conflicting criteria. The design of the layout of hybrid vehicles is formulated as a bilevel decomposed problem including a vehicle level and a battery level in concert with the specialization of the respective design teams required at each level. An iterative algorithm, the Multiobjective Decomposition Algorithm (MODA) is proposed, whose generated sequences are shown to converge to efficient designs for the overall design problem under certain conditions examined in the context of the block coordinate descent method and the method of multipliers. MODA applied to the hybrid electric design problem captures the bilevel tradeoffs originating by the conflicting objectives at the vehicle and battery levels.
Keyword:
Distributed computation
Efficient designs
Pareto equitable
Block coordinate descent
Morphing components
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