ABSTRACT
As a subject of engineering economics, investment analysis plays an important role and use analysis techniques in the solution process. Present worth analysis, return of investment, and cost/benefit analysis are the most popular investment analysis techniques in engineering economics. However, since some investment values are determined by humans/experts and these values are based on human thoughts, it is very difficult to specify exact values. In this way, fuzzy logic can be a better alternative for calculating vagueness in engineering economics' applications. Thus, uncertain cash flows, indefinite life, and indefinite time value of money require to use fuzzy present worth analysis. As a new extension of fuzzy sets, spherical fuzzy sets have stronger capabilities to model uncertain information in investment analysis problems. In this article, spherical fuzzy present worth analysis method is presented for the first time to address the fuzzy parameters of public emergency hospital investment, which is currently a major subject in Turkey. The public emergency hospital for three locations on the European side of Istanbul is evaluated using spherical fuzzy present worth analysis method. While the best location for the emergency hospital is determined as Kemerburgaz, we also conduct a sensitivity and comparison analysis in order to show the robustness and applicability of the proposed method.
ABSTRACT
As an important part of the sharing economy, the usage of car sharing increases world widely with the help of developments in the technology. Especially after COVID-19 the demand for private car ownership and car sharing systems increased tremendously. Therefore, its market share attracts new investors and causes existing service providers to enlarge their service area. In this article, a novel multi-objective location-dependent two-stage stochastic optimization model is proposed to determine the most appropriate locations for car sharing system and allocate the demand to these locations. The model is applied to determine the best locations among 15 candidates, and three objectives are considered, which are the minimization of total cost that comprises locating costs minus income from satisfying the demand, minimization of CO<formula><tex>$_2$</tex></formula> emission occurs by the usage of car sharing system's cars and minimization of average unsatisfied demand. Both location-independent and location-dependent demands are taken into account. The proposed model delivers a more precise decision process framework for problems include stochasticity and multiobjectivity, and it easily can be implemented to any region, providing region sensitive parameters. IEEE
ABSTRACT
The Covid-19 pandemic has brought too many concerns in businesses whether they will survive or fail. This is what makes forecasting crucial since it guides businesses in order to make appropriate decisions. In a pandemic environment, forecasting is critical because there is little historical data available. Taking this into consideration, in this study, fuzzy time series (FTS) and grey model (GM), which do not require long past time series data are implemented for short term forecasting of a product sold on a dedicated social media account. After adopting monthly sales data of the related product, accuracy of fuzzy time series and grey model are improved with parameter optimization. According to the results of absolute percentage error (APE), both methods demonstrate superior forecasting accuracies when the product shows an increasing sales trend. This study can also be a reference for businesses that are positively affected by the pandemic due to increased sales and willing to act on the opportunities it has already emerged. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.