Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2024Scopus SJRQ1/r/munzur/1705
  Integrating discrete-event simulation and artificial intelligence for shortening bed waiting times in hospitalization departments during respiratory disease seasons

  Ortiz-Barrios, Miguel; Ishizaka, Alessio; Barbati, Maria; Arias-Fonseca, Sebastián; Khan, Jehangir; Gul, Muhammet; Yücesan, Melih; Alfaro-Saíz, Juan-Jose; Pérez-Aguilar, Armando

  Seasonal Respiratory Diseases (SRDs) usually produce a heightened number of Emergency Department (ED) attendances due to their rapid dissemination within the community and the ineffective prevention measures. Such a context requires effective management of the emergency care processes to provide in-time diagnosis and treatment to infected patients. Nonetheless, EDs have evidenced severe operational deficiencies during these periods, thereby provoking extended bed waiting times in Hospitalization Departments (HDs). Therefore, this paper presents a hybrid approach merging Artificial Intelligence (AI) and Discrete-Event Simulation (DES) to shorten the bed waiting times in HDs considering patient records collated in the first emergency care stages. First, we implemented Random Forest (RF) to estimate the probability of respiratory worsening based on sociodemographic and clinical patient data. Second, we inserted these probabilities into a DES model mimicking the emergency care from the admission to the HD. We then pretested different HD configurations and strategies seeking to reduce the HD bed waiting time. A case study of a European hospital group was used to validate the suggested framework. The AI-DES model enabled decision-makers to identify an improvement proposal with hospitalization bed waiting time lessening, oscillating between 7.93 and 7.98 h.

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  AtıfScopus16·OpenAlex17

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• MakaleYalnız künye2021Scopus SJRQ1/r/munzur/2864
  Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making

  Lo, Huai-Wei; Liaw, Ching-Fang; Gul, Muhammet; Lin, Kuan-Yu

  Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.

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  AtıfScopus67·WoS56·OpenAlex64

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• MakaleYalnız künye2019Scopus SJRQ1/r/munzur/3765
  Measuring development levels of NUTS-2 regions in Turkey based on capabilities approach and multi-criteria decision-making

  Ozdemir, Yasal; Gul, Muhammet

  Regional development seeks to better understand the issues and problems facing the regions because of the contemporary economic and social changes, including the formulation of territorial policies accordingly. In Turkey, in order to coordinate regional development, 26 regional development agencies were founded relating to the nomenclature of territorial units for statistics-2 (NUTS-2) regions. Since these regions have different development levels, it is useful for stakeholders to determine performance measures related to the regional development and propose a ranking model among these regions to provide a balance in delivering financial support mechanisms. Therefore, in this study, an iterative multi-criteria decision-making (MCDM) model is proposed. Firstly, Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) is used to assign weights to indicators of well-being index for provinces (WiP) in Turkey. Then, a TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) based ranking model for 26 regions was applied. Also, this model takes capabilities and well-being approach into account differently from traditional utilitarian development models which take only some macro-economic and financial parameters. In order to do this, the model uses data from WiP. On conclusion, a comparative ranking projection with two other MCDM methods and WiP is provided and an effective and broader point of view was gained by the regional development performance measuring model.

  AtıfScopus31·WoS25·OpenAlex34

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• MakaleYalnız künye2016Scopus SJRQ1/r/munzur/3946
  An outranking approach based on interval type-2 fuzzy sets to evaluate preparedness and response ability of non-governmental humanitarian relief organizations

  Celik, Erkan; Gumus, Alev Taskin

  After a disaster occurs, national and international non-governmental humanitarian relief organizations (NGOs), as well as the governmental humanitarian relief organizations (GOs), are involved in carrying out the humanitarian relief operations because of insufficiency in recourses such as lack of equipment and human resources. GOs and NGOs play a crucial role in preparedness and response to natural disasters, especially when available resources of them are not enough. The preparedness and response ability of GOs and NGOs aim to minimize the losses and number of affected people. Therefore, the preparedness and response ability of NGOs are becoming more important to support governmental relief activities. In this paper, a hybrid approach, that consists of interval type-2 fuzzy sets, AHP and PROMETHEE, is proposed to evaluate emergency preparedness and response ability performances of NGOs. The proposed hybrid approach is applied to NGOs in Turkey to evaluate their performances, and is conducted in three phases: (1) determination of critical success factors (CSFs) of humanitarian relief logistics management operations, (2) application of interval type-2 fuzzy AHP for obtaining importance weights of CSFs and (3) application of PROMETHEE based on interval type-2 fuzzy sets to evaluate preparedness and response abilities of NGOs. (C) 2016 Elsevier Ltd. All rights reserved.

  AtıfWoS44·OpenAlex55

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