Supplier Selection Fuzzy Model in Supply Chain Management:Vietnamese Cafe Industry Case

Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization.Choosing the right supplier can help businesses increase productivity,competitiveness in the market,and profits without having to lower the quality of the products.However,choosing a supplier is not a simple matter,it requires businesses to consider many aspects about their suppliers.Therefore,the goal of this study is to propose an integrated model consisting of two models:Fuzzy Analytics Network Process(Fuzzy-ANP)model and Weighted Aggregated Sum Product Assessment(WASPAS)to solve the problem above.The Fuzzy-ANP model was developed to evaluate the weightings of the supplier selection criteria,and the WASPAS Model was used to rank the suppliers.An example of supplier selection in the coffee industry in Vietnam was studied to validate the model,namely 5 main criteria,with 16 sub-criteria,and 7 suppliers.The model test results show that the Fuzzy ANP and WASPAS integration model was suitable.In future,these developing models can apply to other industries or integrate with other models.

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain.Open Banking(OB)is one of the most important milestones since the beginning of financial technology innovation and service supply chain.As these are activities provided by traditional banks,non-bank financial institutions also provide financial service with access to consumer banking,transactional and other financial data to develop financial applications and services tailored to their customers.The development of financial technology,“Open banking”,promotes financial services to begin this transformation.However,evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored.Thus,the authors in this research proposed a hybrid multicriteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process(SF-AHP)model and a Multi-Attributive Ideal-Real Comparative Analysis(MAIRCA)model with supports from seasoned domain experts.The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners.The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.

Fuzzy MCDM Model for Selection of Infectious Waste Management Contractors

Healthcare supply chains are under pressure to drive down costs because of digital business,shifting customer needs and new competition.Medical waste generated from medical facilities includes medical activities and daily-life activities of patients and their family members.According to statistics of the Department of Health EnvironmentalManagement,Vietnam currently has more than 13,500 medical facilities,including hospitals from central to provincial and district levels and private hospitals and medical facilities.Preventive medicine generates about 590 tons of medical waste/day and is estimated to be about 800 tons/day.Medical waste includes ordinary medical waste and hazardous medical waste;in which ordinary medical waste accounts for about 80%–90%,only about 10%–20%is hazardous medical waste including infectious waste and non-infectious hazardous waste.This is an environmental and occupational health issue that needs attention in developing countries like Vietnam.Handling large amounts of medical waste to ensure environmental and personal hygiene,doing so inefficiently creates potential hazards to the environment and increases operating costs.However,hospitals lack objective criteria and methods to evaluate and select the most optimal infectious medical waste,relying instead on their own subjective assessment and prior experience.Therefore,the author proposed a fuzzy multicriteria decision making(MCDM)model including Fuzzy Analytic hierarchy process(FAHP)and the Weighted Aggregated Sum-Product Assessment(WASPAS)for infectious medical waste contractors’selection in this research.The proposed Fuzzy MCDM method is in-tended to provide a more efficient,accurate method in the selection of infectious medical waste contractors than subjective assessment methods,thus reduce potential risks to hospitals.The results of this study can be applied to evaluate and select contractors in other industries.

Prediction of BRIC Stock Price Using ARIMA,SutteARIMA,and Holt-Winters

The novel coronavirus has played a disastrous role in many countries worldwide.The outbreak became a major epidemic,engulfing the entire world in lockdown and it is now speculated that its economic impact might be worse than economic deceleration and decline.This paper identifies two different models to capture the trend of closing stock prices in Brazil(BVSP),Russia(IMOEX.ME),India(BSESN),and China(SSE),i.e.,(BRIC)countries.We predict the stock prices for three daily time periods,so appropriate preparations can be undertaken to solve these issues.First,we compared the ARIMA,SutteARIMA and Holt-Winters(H-W)methods to determine the most effective model for predicting data.The stock closing price of BRIC country data was obtained from Yahoo Finance.That data dates from 01 November 2019 to 11 December 2020,then divided into two categories-training data and test data.Training data covers 01 November 2019 to 02 December 2020.Seven days(03December 2020 to 11December 2020)of datawas tested to determine the accuracy of the models using training data as a reference.To measure the accuracy of the models,we obtained the means absolute percentage error(MAPE)and mean square error(MSE).Prediction model Holt-Winters was found to be the most suitable for forecasting the Brazil stock price(BVSP)while MAPE(0.50)and MSE(579272.65)with Holt-Winters(smaller than ARIMA and SutteARIMA),model SutteARIMA was found most appropriate to predict the stock prices of Russia(IMOEX.ME),India(BSESN),and China(SSE)when compared to ARIMA and Holt-Winters.MAPE andMSE with SutteARIMA:Russia(MAPE:0.7;MSE:940.20),India(MAPE:0.90;MSE:207271.16),and China(MAPE:0.72;MSE:786.28).Finally,Holt-Winters predicted the daily forecast values for the Brazil stock price(BVSP)(12 December to 14 December 2020 i.e.,115757.6,116150.9 and 116544.1),while SutteARIMA predicted the daily forecast values of Russia stock prices(IMOEX.ME)(12 December to 14 December 2020 i.e.,3238.06,3241.54 and 3245.01),India stock price(BSESN)(12 December to 14 December 2020 i.e.,.45709.38,45828.71 and 45948.05),and China stock price(SSE)(11 December to 13 December 2020 i.e.,3397.56,3390.59 and 3383.61)for the three time periods.

Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain

Fertilizer industry in Vietnam and globally have entered the saturation phase.With the growth rate slowing down,this poses challenges for the development impetus of the fertilizer industry in the next period.In fact,over the past few decades,Vietnam’s crop industry has abused excessive investment in chemical fertilizers,with organic fertilizers are rarely used or not at all,limiting crop productivity,increasing pests and diseases.To develop sustainable agriculture,Vietnam’s crop industry must limit the use of chemical fertilizers,increase the use of environmentally friendly organic and natural mineral fertilizers to produce clean agricultural products which is safe.Therefore,it is necessary to consider and choose the right supplier to ensure the goal of sustainable development.Spherical Fuzzy Analytic Hierarchy Process(SF-AHP),and the combinative distance-based assessment(CODAS)are new Multicriteria Decision Making(MCDM)method which can be used to solve supplier selection problem.This paper uses an effective solution based on a combined the concept of triple bottom line(TBL),SF-AHP and CODAS approach to help agriculture companies that need to select the best fertilizer supplier.This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs,but also develop sustainable agriculture.

Fuzzy Multi-Criteria Decision Making for Solar Power Plant Location Selection

Vietnam is one of Southeast Asian countries with a rapid GDP growth rate,ranging from 6.5%to 7%annually,leading to an average increase in energy demand of 11%per year.This demand creates many new opportunities in the energy industry,especially renewable energy,to ensure sustainable development in the future for the country with applications of solar energy growing at the present,and other opportunities to expand in the future.In Vietnam,thanks to favorable weather,climate,terrain characteristics and many preferential support policies,there are many great opportunities in the field of solar energy exploitation and application.Location selection is an important problem in all renewable energy projects.Therefore,the author proposed a fuzzy Multi-criteria Decision-Making Model(MCDM)model for solar power plant location selection in this study,and as a result,location 5 is the optimal solution.The contribution of this study is to propose a MCDM for solar power plant location selection in Vietnam under fuzzy environmental conditions.

A Truck Scheduling Problem for Multi-Crossdocking System with Metaheuristics

The cross-docking is a very important subject in logistics and supply chain managements.According to the definition,cross-docking is a process dealing with transhipping inventory,in which goods and products are unloaded from an inbound truck and process through a flow-center to be directly loaded onto an outbound truck.Cross-docking is favored due to its advantages in reducing the material handing cost,the needs to store the product in warehouse,as well decreasing the labor cost by eliminating packaging,storing,pick-location and order picking.In cross-docking,products can be consolidated and transported as a full load,reducing overall distribution costs.In this paper,we focus on a truck scheduling at the multidoor,multi-crossdocking network with inventory constraints and process capability constraints.In this model,a truck can visit severals docks for loading or unloading many types products.This situation is very common in reality.This study also developed an exact mathematical model using mixedinteger linear programming(MILP)with the objective of minimizing the makespan to obtaint the benchmark in small scale problems.Large scale problems are solved through Simulated Annealing(SA)algorithm and Tabu Search(TS)algorithm.Performance of these algorithms will be compared to benchmarks obtained from solver as well as to each other.

Marketing Strategies Evaluation and Selection for Supply Chain Management Under Uncertainty

Sustainable marketing,often known as green marketing,has grown in popularity over the last two decades.Government is currently putting pressure to encourage firms to become environmentally aware in multiple aspects like human and financial utilization,advertisement,and product movement.Different types of companies are including many environmental campaigns into their own products to take advantage of the problem.Although many scholars have addressed the relevance of green marketing as well as theory development,this study is unique in that it examines both techniques in a fuzzy context.The integrated Fuzzy Multicriteria Decision Making Model(MCDM)of the analytical hierarchy process(AHP)and a Portuguese-acronymous MCDM method(TODIM)are used to select the best marketing strategy from five alternatives:(i)Green Design,(ii)Green Positioning,(iii)Green Pricing,(v)Green Packaging,and(iv)Green Disposal.based on criteria such as the scale of the green market,price parity,and the commitment of top management.AfuzzyMCDMmodel for evaluating green marketing strategies was established in the study as contributions for decisionmakers in this field under unclarified circumstances.This research also a useful guideline for ranking alternatives in others industry.

Optimization Agricultural Supply Chain:A Case Study of Fertilizer Supplier Selection

The 21st century is associated with the IndustrialRevolution 4.0 and the organic agriculture trend,making the utilization of high-quality fertilizers,abundant nutritional content,economical,and no affect to environment pollution.According to the new concept,clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers,and plant protection drugs,but priority is to use manure,organic fertilizers,and natural mineral fertilizers.Fertilizer must meet the balanced nutritional requirements of crops,maintain,and improve the fertility of the ground,protect the surrounding ecosystem,and leave harmful effects in agricultural products,products with high quality,safe for users and high economic efficiency for producers.To achieve the above goal,the selection of a fertilizer supplier is an important decision,supporting the supply chain’s sustainable development,fertilizer supplier selection is a multicriteria decision making model,the decision maker must assess all qualitative and quantitative factors.In this paper,the author proposed an integer decision making model including Fuzzy Analytic Hierarchy Process(FAHP)and Complex Proportional Assessment of Alternatives(COPRAS)for fertilizer supplier selection.The weightings of the criteria are calculated by using FAHP,COPRAS is then applied for ranking some potential fertilizer suppliers.The efficiency of the proposed models is proved by a case study conducted in a farm located in the south of Vietnam.This research is the first fertilizer supplier evaluation and se-lection model in Vietnam by interviewing experts and reviewing the literature.Re-search result is to provide a case study on evaluating supplier in agricultural supply chain utilizing the model proposed by the combination of FAHP and COPRAS models.