Analyzing Inter-objective Relationships: A Case Study of Software Upgradability

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9921)

Abstract

In the process of solving real-world multi-objective problems, many existing studies only consider aggregate formulations of the problem, leaving the relationships between different objectives less visited. In this study, taking the software upgradability problem as a case study, we intend to gain insights into the inter-objective relationships of multi-objective problems. First, we obtain the Pareto schemes by uniformly sampling a set of solutions within the Pareto front. Second, we analyze the characteristics of the Pareto scheme, which reveal the relationships between different objectives. Third, to estimate the inter-objective relationships for new upgrade requests, we build a predictive model, with a set of problem-specific features. Finally, we propose a reference based indicator, to assess the risk of applying single-objective algorithms to solve the multi-objective software upgradability problem. Extensive experimental results demonstrate that, the predictive models built with problem-specific features are able to predict both algorithm independent inter-objective relationships, as well as the algorithm performance specific indicator properly.

Keywords

Pareto front Meta-learning Empirical analysis 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Zhilei Ren
    • 1
  • He Jiang
    • 1
  • Jifeng Xuan
    • 2
  • Ke Tang
    • 3
  • Yan Hu
    • 1
  1. 1.Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of SoftwareDalian University of TechnologyDalianChina
  2. 2.State Key Laboratory of Software EngineeringWuhan UniversityWuhanChina
  3. 3.School of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina

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