An integrated model for supplier evaluation in supply chains

U ovom radu predložen je model za vrednovanje i izbor dobavljača koji je razmatran u više od deset različitih proizvodnih oblasti. Model se sastoji od dvadeset kvantitavnih i kvalitativnih kriterijuma koji su primenom fuzzy AHP (Analitičko Hijerarhijski Proces) metode, a na osnovu ocenjivanja menadžera proizvodnih kompanija smanjeni na ukupno devet. Verifikacija datog modela predstavljena je kroz vrednovanje i izbor dobavljača u tri kompanije koje se bave različitom delatnošću. Pored doprinosa koji se ogleda u primenjivosti razvijenog modela u različitim lancima snabdevanja, veliki doprinos ovog rada je razvoj novih pristupa u oblasti višekriterijumskog odlučivanja koji može biti primenjen u svim lancima snabdevanja, naročito u procesima u kojima vladaju neizvesnosti i nejasnoće što je detaljno objašnjeno kroz rad.In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria which are reduced to a total of nine by the application of the fuzzy AHP (Analytic Hierarchy Process) method and the assessment of managers in production companies. The verification of the given model is presented through the evaluation and supplier selection in three companies that deal with different activities. In addition to the contribution reflected in the applicability of the developed model in various supply chains, the great contribution of this paper is the development of new approaches in the field of multi-criteria decision making that can be applied in all supply chains, especially in processes that are subject to uncertainty and vagueness, which is explained in detail through the work

An integrated model for supplier evaluation in supply chains

U ovom radu predložen je model za vrednovanje i izbor dobavljača koji je razmatran u više od deset različitih proizvodnih oblasti. Model se sastoji od dvadeset kvantitavnih i kvalitativnih kriterijuma koji su primenom fuzzy AHP (Analitičko Hijerarhijski Proces) metode, a na osnovu ocenjivanja menadžera proizvodnih kompanija smanjeni na ukupno devet. Verifikacija datog modela predstavljena je kroz vrednovanje i izbor dobavljača u tri kompanije koje se bave različitom delatnošću. Pored doprinosa koji se ogleda u primenjivosti razvijenog modela u različitim lancima snabdevanja, veliki doprinos ovog rada je razvoj novih pristupa u oblasti višekriterijumskog odlučivanja koji može biti primenjen u svim lancima snabdevanja, naročito u procesima u kojima vladaju neizvesnosti i nejasnoće što je detaljno objašnjeno kroz rad.In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria which are reduced to a total of nine by the application of the fuzzy AHP (Analytic Hierarchy Process) method and the assessment of managers in production companies. The verification of the given model is presented through the evaluation and supplier selection in three companies that deal with different activities. In addition to the contribution reflected in the applicability of the developed model in various supply chains, the great contribution of this paper is the development of new approaches in the field of multi-criteria decision making that can be applied in all supply chains, especially in processes that are subject to uncertainty and vagueness, which is explained in detail through the work

AN INTEGRATED SWOT – FUZZY PIPRECIA MODEL FOR ANALYSIS OF COMPETITIVENESS IN ORDER TO IMPROVE LOGISTICS PERFORMANCES

On the question: how to react in a particular situation, the management of the company must have a quick answer. In the time of fast and huge changes in production, the management must know what resources are available in the company and what kind of environment it faces. To respond promptly to the requirements of the environment, the company must define a clear strategy for its business. To define a strategy, management must know the state of the company. From these reasons, in this research it was conducted SWOT analysis of specific company, and after that the elements of the SWOT matrix were ranked using fuzzy PIPRECIA method. This ranking shows on which element company should pay the most attention

Fuzzy Multicriteria Model for Ranking Suppliers in Manufacturing Company

By using the methods of multi-criteria analysis it is possible to make decisions which have significant influence on companies\u27 business. The aim of this paper is to evaluate different suppliers using the integrated model that recognizes a combination of fuzzy AHP (Analytical Hierarchy Process) and the COPRAS method. Based on six criteria, the expert team was formed to compare them, so determination of their significance is being done with fuzzy AHP method. Expert team also compares suppliers according to each criterion and on the base of triangular fuzzy numbers. Based on their inputs, COPRAS method is used to estimate potential solutions. Suggested model accomplishes certain advantages in comparison with previously used traditional models which were used to make decisions about evaluation and choice of supplier. It is vital to make the right decision when selecting a supplier, because the optimal choice ensures lower cost and higher quality of the product itself, and therefore more competitiveness in the market. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Fuzzy Multicriteria Model for Ranking Suppliers in Manufacturing Company

By using the methods of multi-criteria analysis it is possible to make decisions which have significant influence on companies\u27 business. The aim of this paper is to evaluate different suppliers using the integrated model that recognizes a combination of fuzzy AHP (Analytical Hierarchy Process) and the COPRAS method. Based on six criteria, the expert team was formed to compare them, so determination of their significance is being done with fuzzy AHP method. Expert team also compares suppliers according to each criterion and on the base of triangular fuzzy numbers. Based on their inputs, COPRAS method is used to estimate potential solutions. Suggested model accomplishes certain advantages in comparison with previously used traditional models which were used to make decisions about evaluation and choice of supplier. It is vital to make the right decision when selecting a supplier, because the optimal choice ensures lower cost and higher quality of the product itself, and therefore more competitiveness in the market. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

AN INTEGRATED DECISION-MAKING MODEL FOR EFFICIENCY ANALYSIS OF THE FORKLIFTS IN WAREHOUSING SYSTEMS

In the logistics world, special attention should be given to warehousing systems, cost rationalization, and improvement of all the factors that affect efficiency and contribute to smooth functioning of logistics subsystems. In real time industrial practice, the issue of evaluating and selecting the most appropriate forklift involves a complex decision-making problem that should be formulated through an efficient analytical model. The forklifts efficiency plays a very important role in the company. The forklifts are being used on a daily basis and no logistical processes could be done without them. Therefore, it has been decided to determine their efficiency, which will contribute to the optimization of the process in this logistics subsystem. This study puts forward an integrated forklift selection model using Data Envelopment Analysis (DEA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking According to the Compromise Solution (MARCOS) methods. Five input parameters (regular servicing costs, fuel costs, exceptional servicing costs, total number of all minor accidents and damage caused by forklifts) and one output parameter (number of operating hours) were first identified to assess efficiency of eight forklifts in a warehousing system of the Natron-Hayat company using the DEA model. This step allows sorting of efficient forklifts which are subsequently evaluated and ranked using FUCOM and MARCOS methods. A sensitivity analysis is also performed in order to check reliability and accuracy of the results. The findings of this research clearly show that the proposed decision-making model can significantly contribute to all spheres of business applications

Adaptive Fuzzy Model for Determining Quality Assessment Services in the Supply Chain

The problem that is being addressed in this paper is to improve the services provided by company and achieve better communication between companies in the supply chain. Therefore, a qualitative assessment of service has been required. This service is characterized by a group of parameters, which are often inaccurately estimated values, as well as their importance for the evaluation system. This is often the result of assessor´s uncertainty, variability of conditions, etc. Therefore, in the context of AM4SCM (Adaptive Model for Supply Chain Management) a mathematical model for evaluating the quality of services has been developed (FAM4QS - Fuzzy Aggregation Method for Quality Service) which is based on the fuzzy arithmetic. Selection of different values for the degrees of fuzzy power mean, which are used for evaluation of parameters or groups of parameters of the system and the service, contributes to a better assessment and it is due to the varying nature of the parameters. The observed model was simulated on 17 supply chains on the territory of the Republic of Serbia. Service quality assessment is carried out based on data from the user requirements - participants of supply chains binding the so-called fuzzy aggregation function

IMPACT OF THE NUMBER OF VEHICLES ON TRAFFIC SAFETY: MULTIPHASE MODELING

Traffic safety is one of the key issues nowadays, given the fact that a large number of people lose their lives in traffic accidents every day. There are various influential factors in the occurrence of traffic accidents, the number of vehicles being one of them. This paper assesses the traffic safety in Montenegro in the period 1998-2020 by applying the multiphase modeling with a purpose to obtain comparative results which enable implementation of adequate strategies. A total of six scenarios were formed with two inputs and two outputs in a DEA (Data Envelopment Analysis) model, with the number of registered vehicles per year being an input in all scenarios. In addition, as inputs, the scenarios included AADT (Annual Average Daily Traffic), passengers in road transport, passenger-km by road transport, goods transported by road, tone-km by road, and passengers in local transport. The number of traffic accidents with casualties, the number of traffic accidents with material damage, the number of fatal cases and the number of injured persons, depending on a scenario, were observed as outputs. After the DEA model, IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to determine the weights of inputs and outputs, while the final state of traffic safety by years was determined using the MARCOS (Measurement of alternatives and ranking according to COmpromise solution) method

Neuro-fuzzy inference systems approach to decision support system for economic order quantity

Supply chain management (SCM) has a dynamic structure involving the constant flow of information, product, and funds among different participants. SCM is a complex process and most often characterized by uncertainty. Many values are stochastic and cannot be precisely determined and described by classical mathematical methods. Therefore, in solving real and complex problems individual methods of artificial intelligence are increasingly used, or their combination in the form of hybrid methods. This paper has proposed the decision support system for determining economic order quantity and order implementation based on Adaptive neuro-fuzzy inference systems - ANFIS. A combination of two concepts of artificial intelligence in the form of hybrid neuro-fuzzy method has been applied into the decision support system in order to exploit the individual advantages of both methods. This method can deal with complexity and uncertainty in SCM better than classical methods because they it stems from experts’ opinions. The proposed decision support system showed good results for determining the amount of economic order and it is presented as a successful tool for planning in SCM. Sensitivity analysis has been applied, which indicates that the decision sup- port system gives valid results. The proposed system is flexible and can be applied to various types of goods in SC

Green Strategies in Mobility Planning Towards Climate Change Adaption of Urban Areas Using Fuzzy 2D Algorithm

Urban mobility planning must urgently confront the challenges attendant to the low carbon transition and green transformation. The necessary paradigm shift from the traditional approaches to embracing environmental sustainability requires maintaining a firm and stable balancing act between opposing forces. The policy-making process in the transition period is complex and requires a detailed analysis that the academic literature lacks. This study analyzes the decision-making process for urban mobility planning to contribute the academic literature on sustainable transitions. In order to illustrate the complexities in the decision-making process, we design an original case scenario. In the case, the planners are supposed to choose the best project from among four recent green strategies. In the process, they need to take the conflicting requirements on the social, economic, environmental and technical issues into account. Sixteen constraints reflect the available physical and financial conditions. Because the decision-making process includes complexities, a novel two-stages model is introduced in the method that is used to solve the problem. In the first stage, the fuzzy D PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) algorithm is applied to determine the weights. In the second stage, the fuzzy D Dombi (fuzzy 2D) algorithm is proposed to evaluate the alternatives. The results show that societal dynamics are crucially important in choosing the best alternative. Among four alternatives, the one that is inclusive and makes the existing investments more efficient is highly prioritized. Our findings offer policy implications emphasizing the importance of green mobility projects that favors the social benefits as well as financial issues