RESUMEN
Organizations will be increasingly concerned about maintaining their positions in today's changing world, the high-tech era, and the emergence of innovative technologies because of the industrial revolutions. Everyone has come to believe that to survive and continue their constructive roles, they must achieve competitive advantages by working based on the trends. It is undeniable that the introduction of Industry 4.0 has had a significant impact on enterprises, organizations, and, of course, supply chains. In the meantime, selecting a supplier is one of the main strategic decisions of the organization because choosing the right supplier leads to increasing profitability, improving market competition, better accountability, enhancing product quality, and reducing costs. While the issue of supplier evaluation has been one of the interesting topics for researchers in recent decades, its development in the fourth supply chain generation needs further consideration. In this regard, current technologies in the fourth-generation industrial revolution, methods, and criteria used in previous studies based on industry 4.0 and before that are reviewed separately. By reviewing previous articles and experts' opinions, thirteen sub-criteria considering industry 4.0 have been identified for selecting suppliers in three categories, economic, environmental, and social. The weight of each criterion has been determined using a set of fuzzy cognitive maps (FCMs) and considering the centrality of criteria in the concept of communication networks. To prioritize the suppliers, the hesitant fuzzy linguistic term sets (HFLTS) VIKOR method has been used in hesitant fuzzy linguistic terms. Finally, a case study is introduced to illustrate the effectiveness and usefulness of our integrated methodology and prioritize its four suppliers.
Asunto(s)
Toma de Decisiones , Lógica Difusa , Industrias , Lingüística , CogniciónRESUMEN
The amount of municipal solid waste (MSW) has been increasing rapidly in the urban centres of developing countries during the last few decades; however, municipal solid waste management (MSWM) remains inadequate. One of the largest aspects of cost of the MSWM system is the collection of waste. This paper describes a methodology that combines geographic information systems (GIS), hesitant fuzzy linguistic term set (HFLTS), and the full multiplicative form of multi-objective optimization by ratio analysis (MULTIMOORA), to determine suitable locations for waste collection boxes (named AYPIKUT), which have been designed specifically for collection of domestic waste vegetable oil and waste batteries. It takes as case study, Atakum, a district of Samsun city, Turkey. As a solution to the problem, first, a total of 88 items have been identified for consideration by seven criteria elicited from the insights of experts, and spatial analyses were performed. Multi-criteria HFLTS was then used to determine weights of the criteria. Population density was the most significant criterion affecting the selection process, and proximity to housing complexes with more than 150 dwellings was the least important. According to the weights of the seven criteria, and three rules determined by the experts, 15 AYPIKUT locations were identified using GIS. As a final step, the alternative locations (A1-A15) were ranked with the MULTIMOORA method. A5 was the most suitable site, and A6 was the least suitable site for an AYPIKUT. The results indicated the ability of the proposed model to select the suitable locations for waste collection box.
Asunto(s)
Eliminación de Residuos , Administración de Residuos , Ciudades , Sistemas de Información Geográfica , Aceites de Plantas , Residuos Sólidos , Turquía , Instalaciones de Eliminación de ResiduosRESUMEN
There are many criteria to be considered in environmental, social, and economic issues for the landfill site selection (LSS). Multi-criteria decision analysis (MCDA) methods are often used to solve complex decision-making problems such as LSS. However, decision-makers (DMs) may hesitate during the evaluation of the landfill sites with possible incorrect evaluation concerns. Therefore, the inclusion of the hesitant fuzzy linguistic term sets (HFLTS), which considers the hesitations in the preferences of DMs, is suitable for the solution of the problem. On the other hand, geographic information systems (GIS) is an important decision support tool that can analyze different types of spatial data. The aim of this study is to evaluate landfill sites. To do so, the applied approach includes the processes of identifying appropriate alternative sites for landfills by combining HFLTS-based MCDA method and GIS and evaluation of alternative sites with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The applicability of the proposed approach is tested on Samsun city, Turkey. As a result, scenario analysis, which is dominated by environmental criteria, provides better results dominated by social-economic criteria. Consequently, 12 alternative locations are selected and evaluated for the LSS. Atakum and Canik districts of Samsun city are determined as very suitable locations for landfill sites.