Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Fuzzy logic. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method

Abstract: Landfill site selection is a complex and time-consuming process, which requires evaluation of several factors where many different attributes are taken into account. Decision makers always have some difficulties in making the right decision in the multiple attribute environments. After identifying candidate sites, these sites should be ranked using decision-making methods. This study applies Chang’s fuzzy AHP-based multiple attribute decision-making (MADM) method for selection of the best site of landfills based on a set of decision criteria. The Fuzzy Analytic Hierarchy Process (FAHP) was designed to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria. Analytic Hierarchy Process (AHP) is used to make pairwise comparisons and assign weights to the decision criteria. It is easier for a decision maker to describe a value for an alternative by using linguistic terms and fuzzy numbers. In the fuzzy-based AHP method, the rating of each alternative was described using the expression of triangular fuzzy membership functions. Once the global weights of the criteria is calculated by AHP, they are incorporated into the decision matrices composed by decision maker and passed to fuzzy-AHP method which is used to determine preference order of siting alternatives. In this study, a computer program based on the Chang’s fuzzy method was also developed in MATLAB environment for ranking and selecting the landfill site. As an example of the proposed methodology, four different hypothetical areas were chosen and implemented to demonstrate the effectiveness of the program. By using this program, the precision was improved in comparison with traditional methods and computational time required for ranking and selecting the suitable landfill site was significantly reduced.

Particle swarm algorithm for solving systems of nonlinear equations

Abstract: Solving systems of nonlinear equations is one of the most difficult problems in all of numerical computation and in a diverse range of engineering applications. Newton's method for solving systems of nonlinear equations can be highly sensitive to the initial guess of the solution. In this study, a new particle swarm optimization algorithm is proposed to solve systems of nonlinear equations. Some standard systems are presented to demonstrate the efficiency of this method.