On multi-period multi-attribute decision making
Multiple attribute decision making (MADM) is an important part of modern decision science. It has been extensively applied to various areas such as society, economics, military, management, etc., and has been receiving more and more attention over the last decades. To date, however, most research has focused on single-period multi-attribute decision making in which all the original decision information is given at the same period, and a number of methods have been proposed to solve this kind of problems. This paper is devoted to investigating the multi-period multi-attribute decision making (MP-MADM) problems where the decision information (including attribute weights and attribute values) are provided by decision maker(s) at different periods. We define the concept of dynamic weighted averaging (DWA) operator, and introduce some methods, such as the arithmetic series based method, geometric series based method and normal distribution based method, to obtain the weights associated with the DWA operator. Based on the DWA operator, we develop an approach to MP-MADM. Moreover, we extend the DWA operator and the developed approach to solve the MP-MADM problems where all the attribute values provided at different periods are expressed in interval numbers, and use a possibility-degree formula to rank and select the given alternatives.
multi-period multi-attribute decision making (mp-madm) dynamic weighted averaging (dwa) operator arithmetic series based method geometric series based method normal distribution based method