Multi-objective optimization techniques can be categorized globally into deterministic and evolutionary methods. Examples of such methods are the Normal Boundary Intersection (NBI) method and the Strength Pareto Evolutionary Algorithm (SPEA2), respectively. With both methods one explores trade-offs between conflicting performances. Surrogate models can replace expensive circuit simulations so enabling faster computation of circuit performances. As surrogate models of behavioral parameters and performance outcomes, we consider look-up tables with interpolation and Neural Network models.
|Name||Mathematics in Industry|
|Conference||16th European Conference on Mathematics for Industry (ECMI 2010), July 26-30, 2010, Wuppertal, Germany|
|Abbreviated title||ECMI 2010|
|Period||26/07/10 → 30/07/10|