Structural analyses of pareto optimal sets in multi-objective optimization application to window design problem using multi-objective genetic algorithm

Kentaro Suga, Shinsuke Kato, Kyosuke Hiyama

Research output: Contribution to journalArticle


In single-objective optimization problems, which have only one optimal design objective, the absolute optimal solution to maximize/minimize the objective function could be determined. However, in the most of real design problems, optimization problems become multi-objective, which two or more design objectives must be optimized simultaneously, and no single absolute optimal solution is existed. In these cases, recognizing what kind of alternative solutions exist in Pareto optimal sets seems to be useful for designers who have to decide an acceptable solution. In this paper, the authors carried out multi-objective optimization using multi-objective genetic algorithm through a case study involved in the real indoor environmental design - window design. Then the authors analyzed structure of Pareto optimal sets. Here we present the analysis process as well as the case study details, and show how the method proposed here is effective to decide an acceptable solution in multi-objective optimization problem.

Original languageEnglish
Pages (from-to)283-289
Number of pages7
JournalJournal of Environmental Engineering
Issue number625
Publication statusPublished - 1 Mar 2008



  • Design support
  • Luminous environment
  • Multi-objective genetic algorithm
  • Pareto optimal solution
  • Thermal environment

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