Refinement of weights using attribute support for multiple attribute decision making

A number of approaches have been proposed to determine the weights for multiple attribute decision making. However, resultant are usually assumed be fixed, making it lack tolerance accommodate variation if patterns subsequent data subject change. This article proposes a method facilitate adjustment weights, which accommodates relevant characteristics. model is first constructed that able express requirements particular application. The concept support and consensus then weight modification. full algorithm finally presented adjustment. effectiveness validated by way case study in tax credit domain with sensitivity analysis further evaluated.