Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms

DOI10.3934/jimo.2014.10.383zbMath1297.90076OpenAlexW2011581316MaRDI QIDQ380571

Adriel Cheng, Cheng-Chew Lim

Publication date: 14 November 2013

Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/jimo.2014.10.383

zbMATH Keywords

multi-objective optimizationPareto optimizationcoverage driven verificationgenetic evolutionary algorithmssystem-on-chip verification

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Case-oriented studies in operations research (90B90)

Related Items (1)

Non-dominated sorting methods for multi-objective optimization: review and numerical comparison

Cites Work

• Unnamed Item
• Multi-objective aggregate production planning decisions using two-phase fuzzy goal programming method
• Refined necessary conditions in multiobjective optimization with applications to microeconomic modeling
• Nonsmooth optimization over the (weakly or properly) Pareto set of a linear-quadratic multi-objective control problem: explicit optimality conditions
• Markov modelling and parameterisation of genetic evolutionary test generations
• EA for solving combined machine layout and job assignment problems

This page was built for publication: Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms