On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Multidimensional divide-and-conquer
Communications of the ACM
Modeling, Verification, and Exploration of Task-Level Concurrency of Real-Time Embedded Systems
Modeling, Verification, and Exploration of Task-Level Concurrency of Real-Time Embedded Systems
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Pareto-optimization-based run-time task scheduling for embedded systems
Proceedings of the 1st IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Time-Energy Design Space Exploration for Multi-Layer Memory Architectures
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Algorithms to identify pareto points in multi-dimensional data sets
Algorithms to identify pareto points in multi-dimensional data sets
Methods for evaluating and covering the design space during early design development
Integration, the VLSI Journal
ACSD '05 Proceedings of the Fifth International Conference on Application of Concurrency to System Design
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Characterization of Pareto dominance
Operations Research Letters
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Multi-criteria optimisation problems occur naturally in many engineering practices. Pareto analysis has proven to be a powerful tool to characterise potentially interesting realisations of a particular engineering problem. It is therefore used frequently for design-space exploration problems. Depending on the optimisation goals, one of the Pareto-optimal alternatives will be the optimal realisation. It often happens however, that partial design decisions have to be taken, leaving other aspects of the optimisation problem to be decided at a later stage, and that Pareto-optimal configurations have to be composed (dynamically) from Pareto-optimal configurations of components. These aspects are not supported by current analysis methods. This paper introduces a novel, algebraic approach to Pareto analysis. The approach is particularly designed to allow for describing incremental design decisions and composing sets of Pareto-optimal configurations. The algebra can be used to study the operations on Pareto sets and the efficient computation of Pareto sets and their compositions. The algebra is illustrated with a case-study based on transmitting an MPEG-4 video stream from a server to a hand-held device.