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.

Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to normalize the coefficients. However, as different coefficients have different units such as cost or number coefficients, so weighted summation will be meaningless. Furthermore, in most of the studies only quantitative criteria are considered in mathematical model. But, the importance of some qualitative criteria persuade decision maker to consider other affective criteria as well as cost. In this study, in order to ease the problem and to obtain a more reasonable compromised solution for order allocating among suppliers, an integration of analytical hierarchy process and linear integer and multi-objective programming is proposed. The large number of criteria and attributes are employed in this problem and they are employed in a comprehensive model to solve the multi-objective problem and to find the most preferred non dominated solutions by considering decision maker’s (DM) preferences. Some illustrative examples are solved using LINGO and the results are compared. The sensitivity analysis and comparing the results with one of the well-known studies in the literature has demonstrated the flexibility and efficiency of the proposed model to deal with large sized problems and incorporate different purchasing policies, easily and in a short amount of time.

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.

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.

Maintainability plays a fundamental role for achieving success in software system and it is con-sidered as an important quality characteristics. Maintainability may be predicted efficiently by us-ing soft computing techniques as they provide good results. In this paper similarity- based ap-proach is used with the contribution of fuzzy Analytical Hierarchical Process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) at 2-level hierarchy. Here similarity- based approach illustrates the combine approach of fuzzy AHP and fuzzy TOPSIS. This approach is used to provide the rank of software to select the best one for maintainability estimation. Also, several factors are presented that influence the software maintainability. These factors are taken as criterion and three software products are taken as alternatives.

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

With superlative growth in the number of small organizations over the past two decades, the impact caused to environment due to higher production output is also immense. Most governments are continuously taking measures to mitigate the risks associated with industrial growth. One such measure is to implement green practices throughout the supply chain. Since small organizations are important part of supply chain and a major contributor of industrial output they also need to implement green supply chain practices. This paper aims to find out important enablers for green supply chain management (GSCM) from the view point of micro small and medium enterprises (MSMEs). Fuzzy analytical hierarchy process methodology has been used to rank the enablers, three important enablers were identified viz. top management commitment and finance, government support and regulations and recycling and reuse efforts. Managers of small organizations can benefit immensely by focusing on implementing these practices in their organizations.

This paper proposes an application of Analytical Hierarchy Process (AHP) to help decision maker evaluate different processes to identify the weaknesses of an automobile car service where the best alternatives and critical success factors are identified to improve their performances against the market leader. The proposed benchmarking process may help provide effective systematic decision support tool. Thus the endeavor has been made for car service industry to exhibit proposed framework by applying AHP to enhance its competitiveness. The proposed study provides an opportunity to apply to other industries in addition with a diminutive alteration.

Supplier selection management has been considered as an important subject for industrial organizations. In order to remain on the market, to gain profitability and to retain competitive advantage, business units need to establish an integrated and structured supplier selection system. In addition, environmental protection problems have been big solicitudes for organizations to consider green approach in supplier selection problem. However, finding proper suppliers involves several variables and it is critically a complex process. In this paper, the main attention is focused on finding the right supplier based on fuzzy multi criteria decision making (MCDM) process. The weights of criteria are calculated by analytical hierarchical process (AHP) and the final ranking is achieved by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). TOPSIS advantage among the other similar methods is to obtain the best solution close to ideal solution. The paper attempts to express better understanding by an example of an automobile manufacturing supply chain.

Nowadays, the issue of “globalization” is entering to all areas in the world. In addition to products and companies, cities and countries also have the opportunity to see themselves as important actors in international arena. Places define their positions in different fields like business, leisure and recreation, educational opportunities, living, etc. This paper presents an empirical study to introduce city branding as one of the solutions to join globalization process. The method of this research is based on the “descriptive-analytic” and utilize the available literature and experts’ opinions to prioritize the influencing factors of city branding. We use Delphi consensus methods and technique of analytical hierarchy process to evaluate the factors. Finally, the results of the study indicate that security, transportation and mental creativity are the weakest fields and business and shopping facilities are strong fields of city branding in metropolitan of Tehran.