Multicriteria programming in medical diagnosis and treatments

Crina Grosan, Ajith Abraham*, Stefan Tigan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


This paper deals with a special case of multicriteria optimization problems. The problems studied come from the medical domain and are of a very important practical relevance. One of the problems refers to the ranking of treatments for the Trigeminal Neuralgia. The second problem refers to a hierarchy of risk factors for Bronchial Asthma. The most common way to deal with a multiobjective optimization problem is to apply Pareto dominance relationship between solutions. But in the cases studied here, a decision cannot be made just by using Pareto dominance. In one of the experiments, all the potential solutions are nondominated (and we need to clearly find a hierarchy of these solutions) and in the second experiment most of the solutions are nondominated between them. We propose a novel multiple criteria procedure and then an evolutionary scheme is applied for solving the problems. Results obtained by the proposed approach in a very simple way are same as the results (or even better) obtained by applying weighted-sum method. The advantage of the proposed technique is that it does not require any additional information about the problem (like weights for each criteria in the case of weighted-sumapproach).

Original languageEnglish
Pages (from-to)1407-1417
Number of pages11
JournalApplied Soft Computing Journal
Issue number4
Publication statusPublished - Sept 2008


  • Bronchial asthma
  • Evolutionary algorithm
  • Medical diagnosis
  • Multicriteria analysis
  • Pareto dominance
  • Trigeminal neuralgia
  • Weighted sum method


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