A NOVEL TYPE OF FLEXIBLE SOFT ANALYTIC NETWORK PROCESS TO SOLVE THE MULTIPLE-ATTRIBUTE DECISION-MAKING PROBLEM

  Research and development of scientific and technological products have been changing with each passing day in this new millennium. Decisions related to the production of technical products are the key to affecting the sustainable development and market share of enterprises. However, the decision-making related to the production of technology products contains many different evaluation criteria as well as qualitative and quantitative evaluation attributes. Moreover, the correlation between criteria must be considered so it can be treated as a complex multiple-attribute decision-making (MADM) problem. Moreover, performing a multi-attribute decision evaluation often encounters incomplete or missing information provided by experts, which will lead to difficulties in the solution process. In view of the incomplete or missing information of the assessment data, the traditional analytic network process (ANP) method and decision-making trial and evaluation laboratory ANP (DANP) method will delete the incomplete information during the process of assessment and decision-making, and this will bring about non-objective assessment results. In order to solve the above problems, this study proposes a novel type of flexible soft ANP (SANP) method to solve the MADM problems and uses a practical example of smartphone text entry to prove the effectiveness and suitability of the proposed SANP method

Determination of the right medical equipment supplier using the EDAS and WASPAS methods

Bu çalışmanın amacı bir sağlık kuruluşunda yapılan boyun fıtığı, bel fıtığı ve omurga ameliyatlarında kullanılacak olan tıbbi malzemeler için en uygun tedarikçi firmayı belirlemektir. Bu süreçte malzemelerin uygun şekilde tedarikine ilave olarak tedarikçi firmanın da hizmet vermesi gerekmektedir. Bu nedenle kuruluş için, hekim ve hasta memnuniyetini en üst seviyeye çıkaracak tedarikçiyi belirlemek çok önemli olmaktadır. Bu süreç çok kriterli karar verme (ÇKKV) problemi olarak da görülmektedir. Bu nedenle problemi çözmek için ÇKKV yöntemlerinden Step-Wise Weight Assessment Ratio Analysis (SWARA), Evaluation based on Distance from Average Solution (EDAS) ve Weighted Aggregated Sum Product ASsessment (WASPAS) yöntemleri bütünleşik olarak kullanılarak en uygun tedarikçi firma belirlenmiştir. SWARA ile kriter ağırlıkları belirlenirken, EDAS ve WASPAS yöntemleri ile tedarikçiler, kriterler dikkate alınarak değerlendirilmiştir. Ayrıca duyarlılık analizi yapılarak kriter ağırlıklarının tedarikçi seçimindeki olası etkileri ortaya çıkarılmıştır. Yöntemlerin uygulanması neticesinde en uygun tedarikçinin EDAS’a göre T1, WASPAS’a göre ise T2 olduğu belirlenmiştir. T3 her iki yönteme göre de son sırada yer almıştır.The aim of this study was to determine the most appropriate supplier for the medical equipment to be used in cervical disc herniation, lumbar disc herniation, and spine surgeries in a health institution. The supplier was also to provide maintaining services. Thus, determination of the proper supplier was of great importance for the health institution to maximize the satisfaction of the physicians and the patients. It was considered to be a Multi-Criteria Decision Making (MCDM) problem, so the Step-Wise Weight Assessment Ratio Analysis (SWARA), Evaluation based on Distance from Average Solution (EDAS), and Weighted Aggregated Sum Product Assessment (WASPAS) methods were used in an integrated way in the determination process. While the SWARA method was employed in determining the weights for the criteria, the EDAS and WASPAS methods were used in the evaluation process. A sensitivity analysis was also made to reveal the possible effects of the weights on supplier selection. The results demonstrated that the best supplier was T1 according to EDAS, and T2 according to WASPAS, while T3 was in the last place according to both methods

An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains

Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method