Uncertain linguistic information preference ranking ofmulti-objective particle swarm optimization algorithm
一种不确定语言偏好排序的多目标粒子群算法

In order to transfer multi-objectives problem into single objective problem and consider the decision making process of the uncertainty and fuzziness, it transferred uncertain linguistic information into uncertain linguistic variables, and used uncertain linguistic variables algorithm for computing. Then it defined the complementary judgment matrix, used multi-indexes uncertainty sorting method to determine the weights of decision-makers, and transferred discrete levels of objective's attributes to integrated levels and determined the weights of objectives. After that, it made objective's values normalized and defined a uncertain preference integrated fitness function of multi-objectives problem based on these objective weights, and used particle swarm optimization algorithm to solve the multi-objectives problem. Finally, it used a case to illustrate the algorithm's feasibility.