Abstract: Using entropy weight and TOPSIS method, a
comprehensive evaluation is done on the development level of
Chinese regional service industry in this paper. Firstly, based on
existing research results, an evaluation index system is constructed
from the scale of development, the industrial structure and the
economic benefits. An evaluation model is then built up based on
entropy weight and TOPSIS, and an empirical analysis is conducted on
the development level of service industries in 31 Chinese provinces
during 2006 and 2009 from the two dimensions or time series and
cross section, which provides new idea for assessing regional service
industry. Furthermore, the 31 provinces are classified into four
categories based on the evaluation results, and deep analysis is carried
out on the evaluation results.
Abstract: A lot of computer-based methods have been developed
to assess the evacuation capability (EC) of high-rise buildings.
Because softwares are time-consuming and not proper for on scene
applications, we adopted two methods, fuzzy analytic hierarchy
process (FAHP) and technique for order preference by similarity to an
ideal solution (TOPSIS), for EC assessment of a high-rise building in
Jinan. The EC scores obtained with the two methods and the
evacuation time acquired with Pathfinder 2009 for floors 47-60 of the
building were compared with each other. The results show that FAHP
performs better than TOPSIS for EC assessment of high-rise buildings,
especially in the aspect of dealing with the effect of occupant type and
distance to exit on EC, tackling complex problem with multi-level
structure of criteria, and requiring less amount of computation.
However, both FAHP and TOPSIS failed to appropriately handle the
situation where the exit width changes while occupants are few.
Abstract: In this article, by using fuzzy AHP and TOPSIS
technique we propose a new method for project selection problem.
After reviewing four common methods of comparing alternatives
investment (net present value, rate of return, benefit cost analysis
and payback period) we use them as criteria in AHP tree. In this
methodology by utilizing improved Analytical Hierarchy Process
by Fuzzy set theory, first we try to calculate weight of each
criterion. Then by implementing TOPSIS algorithm, assessment of
projects has been done. Obtained results have been tested in a
numerical example.
Abstract: Selection of a project among a set of possible
alternatives is a difficult task that the decision maker (DM) has to
face. In this paper, by using a fuzzy TOPSIS technique we propose a
new method for a project selection problem. After reviewing four
common methods of comparing investment alternatives (net present
value, rate of return, benefit cost analysis and payback period) we
use them as criteria in a TOPSIS technique. First we calculate the
weight of each criterion by a pairwise comparison and then we utilize
the improved TOPSIS assessment for the project selection.