VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

Permutation based decision making under fuzzy environment using Tabu search

One of the techniques, which are used for Multiple Criteria Decision Making (MCDM) is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS) based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method

RANKING TRAVEL AND TOURISM ENABLERS IN INDIA USING A FUZZY APPROACH

This paper seeks to review the enablers for the Travel & Tourism (T&T) industry in India and to rank these factors. The paper aims to introduce a fuzzy TOPSIS approach for this purpose. The paper begins with a literature review to investigate the significant enablers in the T&T sector. The research was conducted among the tourists in the northern state of Uttarakhand, India which is a famous tourist destination both for adventure and pilgrimage. Fuzzy TOPSIS approach is used to meet the objectives of the study. Required information was gathered through a questionnaire. The results show that Safety & Security, Price, Transport and Infrastructure are the most important factors in Indian context.The paper will be helpful in enabling the T&T industry policy makers to identify the key service factors in the sector and take the improvement measuresThe concept of ranking T&T enablers using a Fuzzy TOPSIS is a new approach. The study is the unique application of a fuzzy approach to examine and rank customer expectations of the T&T enablers in Indian context

Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm

By 2025 the Republic of Colombia aims to be an advisory member of the Antarctic Treaty System (ATS) and the installation of a scientific station is necessary to upscale the scientific capabilities. The aim of this paper is showing the results of the implementation of a Fuzzy TOPSIS algorithm for site selection of the Colombian Antarctic Scientific Station. A three-phase methodology was AQ1 proposed, and the obtained results allowed to identify the optimum location for the station, considering key success factors and regulatory constraints

Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs

With the growing number of Web services on the internet, there is a challenge to select the best Web service which can offer more quality-of-service (QoS) values at the lowest price. Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet. In this paper, we modify the interval data envelopment analysis (DEA) models [Wang, Greatbanks and Yang (2005)] for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors. We conduct a set of experiments using a synthesized dataset to show the capabilities of the proposed models. The experimental results show that the correlation between the proposed models and the interval DEA models is significant. Also, the proposed models provide almost robust results and represent more stable behavior than the interval DEA models against QoS variations. Finally, we demonstrate the usefulness of the proposed models for QoS-aware Web service composition. Experimental results indicate that the proposed models significantly improve the fitness of the resultant compositions when they filter out unsatisfactory candidate services for each abstract service in the preprocessing phase. These models help users to select the best possible cloud service considering the dynamic internet environment and they help service providers to improve their Web services in the marke

Pengujian Optimization dan Non-Optimization Query Metode Topsis untuk Menentukan Tingkat Kerusakan Sektor Bencana Alam

The huge volume of data from the Disaster Management Planning and Control (P3B) surveyor team creates wide and varied problems that can consume system resources and processing time that is relatively long. There-fore, this study proposes a solution by performing query optimization on the TOPSIS method which is implemented in a decision support system to determine the level of post-disaster damage. Based on 3 trials with different amounts of data, the 1st trial used 114 data, the 2nd trial used 228 data and the 3rd trial used 334 data. In addition, for each trial, the response time measurement was repeated 3 times, so that the average response time of each step of the TOPSIS method was obtained. It was found that the results of the ranking stage using query optimization were 0.00076 faster than the non-optimization query. So, it can be concluded that the response time obtained by query optimization at each step of the TOPSIS method in the post-natural disaster sector damage decision support system is smaller than the response time in non-optimization queries

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management