In the existing market, companies confront a fierce competition, so the need for new and efficient process for supply chain has become necessarily important. To this end, supply chain management among multi agent system is proposed for addressing the selection and evaluation process related to the inbound logistics. However, most of recent systems deal solely with the negotiation including the selection of one or multiple suppliers, without supporting the transportation provider selection simultaneously and consider it as decision criterion that affect the final choice of cooperative suppliers. As part of win-win negotiation, active supplier involvement can enhance efficiency and effectiveness of supply chain. Then again, transport cost constitutes the most important factor in the third of the total operational costs of a supply chain. To face this challenge, a new form of supplier selection including transportation provider selection is proposed. For this purpose, we present a multi-issue decision protocol based on ontology to support the negotiation between upstream nodes of supply chain in the proposed multi agent system. Furthermore, the automated multi-criteria analysis model based on combined analytical hierarchy process (AHP) and TOPSIS is judged helpful for decision-makers to make quick decision with less human interactions.

Evaluating research productivity of lecturer is a vital process of universities for teaching improvement and administrative decision making. Lecturers’ research productivity evaluation is a difficult and sensitive problem which has many objective and subjective criteria, complexity and imprecision. Therefore, the evaluation of lecturers’ research productivity can be viewed as a multi-criteria decision making (MCDM) problem in vague environment. This study develops an integrated MCDM approach for evaluating the lecturers’ research productivity. In the proposed approach, a fuzzy analytic hierarchy process (AHP) is applied to determine the weights of criteria. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method using interval neutrosophic sets is further adopted for showing the preference order of the lecturers’ research productivity in an educational organization. Finally, the proposed approach is applied to solve the lecturers’ research productivity evaluation problem in the case of University of Economics and Business, Vietnam National University, Hanoi (UEB-VNU).

Performance assessment of teaching competency plays an important role in educational activities. Previous assessments of lecturers’ performance have failed to distinguish between potential capacity and their teaching effectiveness. To solve this problem, the integrated approach of quantitative assessment and multi-criteria decision-making models has become one of the main trends for assessing the performance of lecturers in multiple dimensions: self, peer-, manager- and student-based evaluation. This paper proposes a novel hierarchical approach, developed by the Technique for Order preference by Similarity to Ideal Solution method in an interval-valued complex neutrosophic set environment, to more accurately and comprehensively understand the evaluation process and fit it into a systematic framework. An application is given to illustrate a practical solution in lecturer’s evaluation. The accuracy of the proposed method is verified by comparing with other methods.

Construction emissions have become a major concern that has risen extensively in the last few decades. This paper introduces a building information modeling (BIM)-based model to evaluate the environmental and economic consequences of different project alternatives. The model calculates direct, indirect emissions and primary energy for the overall project life cycle. A hybrid fuzzy multi-objective non-dominated sorting genetic algorithm II (NSGA-II) problem is designed to model the uncertainties associated with the quantification of the judging attributes, and consequently to find the most sustainable materials by minimizing the objective functions; project duration, project life cycle cost, project overall emissions and total project primary energy. Finally, TOPSIS is applied to select the most sustainable material for each construction component among the set of Pareto optimal solutions. A case study of an academic building in Saudi Arabia is presented in order to exemplify the practical features of the proposed model.

In the era of digital manufacturing and highly competitive environment, it is desirable to deliver the right item, right quantity at right time at minimal cost. Under this volatile market environment, the inventory should be readily available at the manufacturing level at the lowest possible cost. Many industries have been conventionally employing traditional ABC analyses based on a single criterion of annual consumption cost for classification of inventory items in spite of other criteria such as unit cost, consumption rate, average inventory cost that may be important in inventory classification. To address such problems, incorporation of Multi-criteria decision making (MCDM) methods is considered an advantage. The present article focuses on a new approach to categorize inventory items using Modified similarity-based method. The proposed method is applied to the inventory data of raw materials from a renowned conveyor belt manufacturing company of West Bengal, India. By using Modified similarity-based method, the items are classified in A, B and C categories. Results obtained from the said method using R program are compared with those of well recognized TOPSIS and AHP methodologies to validate the application of this method for inventory classification.

Green supplier selection is an important group decision making problem that includes not only economic criteria, but also environment and society criteria incorporating vagueness and imprecision. This paper proposes a new integrated quality function deployment (QFD) and technique for order preference by similarity to ideal solution (TOPSIS) using generalized fuzzy numbers. The proposed approach initially identifies the features that the purchased product should possess in order to satisfy the company’s needs (“WHATs”), and then it seeks to establish the relevant supplier assessment criteria (“HOWs”). Then, the importance of the ‘‘WHATs’’, ‘‘HOWs’’, ‘‘HOWs’’-‘‘WHATs’’ correlation scores, and the impact of each potential green suppliers are determined based on generalized fuzzy numbers. The study applies the TOPSIS approach to rank the green suppliers. A numerical example is used to illustrate the advantages and applicability of the proposed approach.

Green or sustainable chemistry, is an area of science focused primarily on development of products and processes to reduce the use and generation of hazardous materials. This paper presents a survey on 15643 articles published on Scopus database over the period 1990-2019. The study uses a multi criteria decision making (MCDM) technique named “The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)” to rank the 20 countries that are responsible for publication of 14870 articles. The study uses three criteria; namely h-index, I-100 and the highest cited article for ranking different countries. The results indicate that India with 2655 articles was considered the first country followed by the United States with 2367, Germany with 611 and United Kingdom with 693 articles.

Decision makers of various disciplines are facing challenges because of vast availability of options in the real world. Even though each and every decision made by a decision maker is being done with a great knowledge and conscience, the decision maker needs suitable support to choose the most favorable option to acquire great results in an agile environment. Supplier selection is imperative for an efficient supply chain management. Many industries are in need of effective decision making tools which aids them in valuable supplier selection. This paper proposes a model using Multi Criteria Decision Making (MCDM) tools viz., Grey Relational Analysis (GRA), Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). GRA is used to shortlist the criteria from the available options, while AHP is used to assign weights to the criteria. The final supplier in the selection process is obtained using TOPSIS. The proposed GRA-AHP-TOPSIS model (GRAHP TOP) is used to analyze and formulate the important criteria and the applicability of the model is tested on a case of a small scale industry located in South India.

The aim of this paper is to apply the technique for order preference by similarity to ideal solution (TOPSIS) as a multi-criteria decision making tool to form the all-time best World XI Test cricket team while taking into consideration over 2600 cricketers participated in Test matches for more than 100 years of cricket history. From the voluminous database containing the performance of numerous Test cricketers, separate lists are first prepared for different positions in the batting and bowling orders consisting of manageable numbers of candidate alternatives while imposing some constraints with respect to the minimum number of innings played (for batsmen), minimum number of tests played (for wicketkeepers and bowlers), and minimum numbers of runs scored and wickets taken (for all-rounders). The TOPSIS method is later adopted to rank those shortlisted cricketers and identify the best performers for inclusion in the proposed World XI Test team. The best World Test cricket team is thus formed as Alastair Cook (ENG) (c), Sunil Gavaskar (IND), Rahul Dravid (IND) (vc), Sachin Tendulkar (IND), Shivnarine Chanderpaul (WI), Jacques Kallis (SA), Adam Gilchrist (AUS) (wk), Glenn McGrath (AUS), Courtney Walsh (WI), Muttiah Muralitharan (SL) and Shane Warne (AUS).

In this paper we develop a fuzzy TOPSIS method based on intuitionistic fuzzy values to solve multiple criteria decision making problems in which the performance rating of alternatives values and the weights of criteria are given by linguistic terms. Arithmetic operations between intuition-istic fuzzy values are used for normalizing imprecise ratings and weights of criteria. In order to demonstrate the effectiveness of the suggested method, we propose a case study aiming to evalu-ate and compare the service quality of five major airports in North Africa. The suggested method helps manager of airports know the needs of passengers and the priority of enhancing service items.