 Multiobjective optimisation of stochastic problems using a mixed metaheuristic and regression techniqueSeyed Hamid Reza Pasandideh and Mahsa Mesgaran International Journal of Mathematics in Operational Research, 2016, vol. 8, issue 1, 96-113 Abstract: Many real word decision making problems involve multi response problems which have stochastic nature. In some cases the relationship between input and output variables is unknown and the regression techniques are used to data generation in this paper. The problem is modelled by four multi objective decision making (MODM) approaches and six structures of genetic algorithm (GA) are developed to solve these models. In structure of these genetic algorithms, six pairwise multiple comparisons statistical tests are used to control the random nature of problems. Finally the algorithms are applied to several polynomial examples and compared their performance statistically considering their accuracy and running times. Furthermore the multi attribute decision making method, simple additive weighting (SAW), is used to find the most desirable algorithm. Keywords: multiobjective stochastic problems; metaheuristics; regression; genetic algorithms; pairwise multiple comparisons; statistical tests; MADM; multiattribute decision making; simple additive weighting; SAW; multiobjective optimisation; modelling. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:8:y:2016:i:1:p:96-113 Access Statistics for this article More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd |
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