Hosting Olympic Games is a significant opportunity for every country and her metropolitan cities. Olympics offer several benefits to the Host countries and cities such as introducing cultural assets of the country to the world and increasing economic value of the country and city Olympics held. Countries and cities wishing to host Olympic Games have to prove that they have the qualifications to be host of these games. The International Olympic Committee (IOC) has identified 5 main criteria and 22 sub-criteria to determine the objectivity measure of this adequacy. These criteria are in conflict with each other so multi-criteria decision making (MCDM) methods can be useful to determine the best host country and its city for Olympic Games. In this study, an integrated MCDM model is proposed to determine the best metropolitan city in Turkey for hosting of the Olympic Games. The contribution of this study is that there are very few studies related to the selection of hosting places for Olympic Games using MCDM methods. The results of the integrated model show that Antalya is the best metropolitan host for Olympic Games.

In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model’s output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed.

Tehran, as one of the most populated capital cities worldwide, is categorized in the group of highly polluted cities in terms of the geographical location as well as increased number of industries, vehicles, domestic fuel consumption, intra-city trips, increased manufacturing units, and in general excessive increase in the consumption of fossil energies. City logistics models can be effectively helpful for solving the complicated problems of this city. In the present study, a queuing theory-based bi-objective mathematical model is presented, which aims to optimize the environmental and economic costs in city logistics operations. It also tries to reduce the response time in the network. The first objective is associated with all beneficiaries and the second one is applicable for perishable and necessary goods. The proposed model makes decisions on urban distribution centers location problem. Subsequently, as a case study, the fruit and vegetable distribution network of Tehran city is investigated and redesigned via the proposed modelling. The results of the implementation of the model through traditional and augmented ε-constraint methods indicate the efficiency of the proposed model in redesigning the given network.

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.

Very recently, Qiupeng and Zuxing (2017) [Qiupeng, G., & Zuxing, X. (2017). A new approach for ranking fuzzy numbers based on possibility theory. Journal of Computational and Applied Mathematics, 309, 674-682.] suggested a new fuzzy ranking technique on the basis of possibility theory. In this note, we show that this method leads to the incorrect result in various cases.

Fuzzy Analytical Network Process (F-ANP) method is able to consider the complex relationships among different levels of decisions, transactions, and feedbacks of criteria and alternatives to calculate the weights of the elements. The large number of pair-wise comparisons in F-ANP and also difficulties in understanding the way of comparisons for the expert, have reduced the efficiency and practicality of this method. In this paper, in order to eliminate the above-mentioned problems, it has been tried to provide an approach using the Fuzzy Best-Worst method, called F-BWANP. The proposed method, requires less comparison data and leads to more consistent comparisons, which means that more reliable results can be obtained, while making it much easier for responding by experts. Finally, in order to describe the proposed method and evaluate its capability, a numerical example is provided.

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).

Optimality and efficiency are two measures that can be used by the system designer to select or compare between different optimal layouts. At the same time, the system designer has three choices of part assignment to cells in accordance with his needs (minimum sum of voids and /or exceptions). Unfortunately, the impact of choosing the type of part assignment on optimality and/or efficiency is not taken into consideration in any previous studies. In this paper, a critical analysis of the impact of part assignment in cellular manufacturing systems is elaborated on three cases borrowed from the literature. In the first case study, different grouping efficiency measures were used on two different optimal distributions having the same number of cells. These measures give different conflict evaluations, for that the designer’s decision to choose the optimal solution depends on the optimality rather than the efficiency. For the second case, the analysis was performed using three types of part assignment on the same optimal system (same number of cells). The results showed that the designer’s decisions depend on the constraints on the shop floor, since there is a conflict between the efficiency and the optimality. For the third case, one type of part assignment was executed on one system with different number of cells and the designer takes his decision based on the efficiency.