Lazim Abdullah

Work place: Faculty of Science and Technology, University Malaysia Terengganu, 21030 K. Terengganu, Malaysia

E-mail: lazim_m@umt.edu.my

Website:

Research Interests: Computer systems and computational processes, Artificial Intelligence, Swarm Intelligence, Medicine & Healthcare, Healthcare

Biography

Lazim Abdullah holds undergraduate B Sc (Hons) in Mathematics at University of Malaya in Jun 1984. He obtained masters degree in Mathematics Education at University of Science Malaysia, Penang in 1999 and Doctorate (Ph.D.) at University of Malaysia Terengganu, in Information Technology Development, September 2004. He is currently Associate Professor at Faculty of Science and Technology, University of Malaysia Terengganu, Ministry of Higher Education Malaysia.  His researches are dealt with fuzzy sets theory and its applications to social ecology, health sciences, economics, environmental sciences and education.  He is interested about measurement of social, health and education indicators by inserting computational intelligence of fuzzy knowledge. His interest also lies towards profiling social and educational constructs using statistical software. He is an editor of books, conferences’ proceedings and also a reviewer and editorial board of International Journals. He is a member of IEEE Computational Intelligence Society, Malaysian Mathematical Society and International Society of Multi Criteria Decision Making.

Author Articles
A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

By Lazim Abdullah Adawiyah Otheman

DOI: https://doi.org/10.5815/ijisa.2013.02.03, Pub. Date: 8 Jan. 2013

Fuzzy Technique for Order Preference by Similarly to Ideal Solution (TOPSIS) is one of the most commonly used approaches in solving numerous multiple criteria decision making problems. It has been widely used in ranking of multiple alternatives with respect to multiple criteria with the superiority of fuzzy set type-1 and subjective weights. Recently, fuzzy TOPSIS has been merged with interval type-2 fuzzy sets and subjective weights for criteria as to handle the wide arrays of vagueness and uncertainty. However, the role of objective weights in this new interval type-2 fuzzy TOPSIS has given considerably less attention. This paper aims to propose a new objective weight for sub-criteria in interval type-2 fuzzy TOPSIS. Instead of using weight for criteria, this paper considers entropy weights for sub-criteria in interval type-2 fuzzy TOPSIS method. An example of supplier selection is used to illustrate the proposed method.

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