Minimum cost strategic weight assignment for multiple attribute decision-making problem using robust optimization approach

In practical multiple attribute decision-making (MADM) problems, the interest groups or individuals intentionally set weights to achieve their own benefits. this case, rankings of alternatives are changed strategically, which is strategic weight assignment problem in MADM. However, cannot be easily and usually need a compensation. Some research denoted compensation as costs assumed that they deterministic. paper, we study based on robust optimization theory, assumes uncertain reside uncertainty sets. With perturbation vector varying box set, ellipsoid polyhedron it allows considered with several different levels. A series mixed 0–1 models constructed for desired ranking particular alternative. Finally, an example actual anti-epidemic performance data from 14 provinces cities illustrates validity proposed models. Comparison between certainty model three unit adjustment always lead higher costs. And further comparative analysis highlights influence will increase levels increase.