eng International Academy of Ecology and Environmental Sciences Computational Ecology and Software 2220-721X 2017-6-1 7 2 38 48 1 article WenJun Zhang YanHong Qi Xin Li 1 2 3 School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; International Academy of Ecology and Environmental Sciences, Hong Kong Sun Yat-sen University Libraries, Sun Yat-sen University, Guangzhou 510275, China College of Plant Protection, Northwest A and F University, Yangling 712100, Shaanxi, China In present study, we developed the software for multi-attribute assessment problems, MATASS (Multi-Attribute Assessment System). The procedures of MATASS include, (1) for a multi-attribute assessment problem, there are m attributes for the assessment of n objects (ecosystems, networks, or habitats, etc.), and each attribute is given a weight according to its importance, and each of the attributes, according to its attribute domain, is assigned to one of seven common types, i.e., interval, upper limit, lower limit, weakly determined value, strongly determined value, no upper and lower limits (the bigger the better), and no upper and lower limits (the smaller the better); (2) data matrix is normalized corresponding to the types of attributes; (3) find the objects that do not meet their specified attribute intervals or values, disqualify these objects and remove them from object list, and the remaining objects are identified as the qualified; (4) re-normalize the data matrix for the qualified objects; (5) assess the qualified objects using various multi-attribute assessment methods, like TOPSIS, REVAWEA, SAWA, etc; (6) determine the final ranking of the qualified objects using Copeland method. Full Matlab codes and software of MATASS were given. http://www.iaees.org/publications/journals/ces/articles/2017-7(2)/MATASS-software-for-multi-attribute-assessment-problems.pdf attributes TOPSIS REVAWEA SAWA Copeland assessment software Matlab