Comparative analysis of two-dimensional data-driven efficient frontier estimation algorithms

Ilya Yuskevich, Rob Vingerhoeds, Alessandro Golkar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In this paper we show how the mathematical apparatus developed originally in the field of econometrics and portfolio optimization can be utilized for purposes of conceptual design, requirements engineering and technology roadmapping. We compare popular frontier estimation models and propose an efficient and robust nonparametric estimation algorithm for two-dimensional frontier approximation. The proposed model allows to relax the convexity assumptions and thus enable estimating a broader range of possible technology frontier shapes compared to the state of the art. Using simulated datasets we show how the accuracy and the robustness of alternative methods such as Data Envelopment Analysis and nonparametric and parametric statistical models depend on the size of the dataset and on the shape of the frontier.

Original languageEnglish
Title of host publication4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538644461
DOIs
Publication statusPublished - 26 Nov 2018
Event4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Roma, Italy
Duration: 1 Oct 20183 Oct 2018

Publication series

Name4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Proceedings

Conference

Conference4th IEEE International Symposium on Systems Engineering, ISSE 2018
Country/TerritoryItaly
CityRoma
Period1/10/183/10/18

Keywords

  • Decision support systems
  • Efficient frontiers
  • Pareto frontiers
  • Requirements engineering
  • Technology planning

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