Comparison on neural networks and support vector machines in suppliers' selection

Suppliers＇ selection in supply chain management （SCM） has attracted considerable research interests in recent years. Recent literatures show that neural networks achieve better performance than traditional statistical methods. However, neural networks have inherent drawbacks, such as local optimization solution, lack generalization, and uncontrolled convergence. A relatively new machine learning technique, support vector machine （SVM）, which overcomes the drawbacks of neural networks, is introduced to provide a model with better explanatory power to select ideal supplier partners. Meanwhile, in practice, the suppliers＇ samples are very insufficient. SVMs are adaptive to deal with small samples＇ training and testing. The prediction accuracies for BPNN and SVM methods are compared to choose the appreciating suppliers. The actual examples illustrate that SVM methods are superior to BPNN.

Application of Intuitionistic Z-Numbers in Supplier Selection

Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees.In contrast,Z-numbers consist of restriction components,with the existence of a reliability component describing the degree of certainty for the restriction.The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers,namely intuitionistic Z-numbers(IZN).The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are charac-terized by the membership and non-membership functions,exhibiting the degree of the hesitancy of decision-makers.This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.A decision-making model is proposed using the trapezoidal intuitionistic fuzzy power ordered weighted average as the aggregation function and the ranking function to rank the alternatives.The proposed model is then implemented in a supplier selection problem.The obtained ranking is compared to the existing models based on Z-numbers.The results show that the ranking order is slightly different from the existing models.Sensitivity analysis is performed to validate the obtained ranking.The sensitivity analysis result shows that the best supplier is obtained using the proposed model with 80%to 100%consistency despite the drastic change of criteria weights.Intuitionistic Z-numbers play a very important role in describing the uncertainty in the decision makers’opinions in solving decision-making problems.

Selection of Wind Turbine Systems for the Sultanate of Oman

The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades,and the government has struggled to find a solution.In addition,Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040,including solar and wind turbines.Furthermore,the use of small-scale energy from wind devices has been on the rise in recent years.This upward trend is attributed to advancements in wind turbine technology,which have lowered the cost of energy from wind.To calculate the internal and external factors that affect the small-scale energy of wind technologies,the study used a fuzzy analytical hierarchy process technique for order of preference by similarity to an ideal solution.As a result,in the decision model,four criteria,seventeen sub-criteria,and three resources of renewable energy were calculated as options from the viewpoint of the Sultanate of Oman.This research is based on an examination of statistics on energy produced by wind turbines at various locations in the Sultanate of Oman.Further,six distinct miniature wind turbines were investigated for four different locations.The outcomes of this study indicate that the tiny wind turbine has a lot of potential in the Sultanate of Oman for applications such as homes,schools,college campuses,irrigation,greenhouses,communities,and small businesses.The government should also use renewable energy resources to help with the renewable energy issue and make sure that the country has enough renewable energy for its long-term growth.

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.

A Novel Green Supplier Selection Method Based on the Interval Type-2 Fuzzy Prioritized Choquet Bonferroni Means

In view of the environment competencies,selecting the optimal green supplier is one of the crucial issues for enterprises,and multi-criteria decision-making(MCDM)methodologies can more easily solve this green supplier selection(GSS)problem.In addition,prioritized aggregation(PA)operator can focus on the prioritization relationship over the criteria,Choquet integral(CI)operator can fully take account of the importance of criteria and the interactions among them,and Bonferroni mean(BM)operator can capture the interrelationships of criteria.However,most existing researches cannot simultaneously consider the interactions,interrelationships and prioritizations over the criteria,which are involved in the GSS process.Moreover,the interval type-2 fuzzy set(IT2FS)is a more effective tool to represent the fuzziness.Therefore,based on the advantages of PA,CI,BM and IT2FS,in this paper,the interval type-2 fuzzy prioritized Choquet normalized weighted BM operators with fuzzy measure and generalized prioritized measure are proposed,and some properties are discussed.Then,a novel MCDM approach for GSS based upon the presented operators is developed,and detailed decision steps are given.Finally,the applicability and practicability of the proposed methodology are demonstrated by its application in the shared-bike GSS and by comparisons with other methods.The advantages of the proposed method are that it can consider interactions,interrelationships and prioritizations over the criteria simultaneously.

Fuzzy Multi-Objective Decision Model of Supplier Selection with Preference Information

Supplier selection is a multi-objective decision problem, which must be considered many objectives, some objectives are qualitative, and others are quantitative. Meanwhile, manufacturer has preference for different suppliers. In this paper, a new multi-objective decision model with preference information of supplier is established. A practical example of supplier selection problem utilizing this model is studied. The result demonstrates the feasibility and effectiveness of the methods proposed in the paper.

A New Decision-Making Model Based on Plithogenic Set for Supplier Selection

Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability.The choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision based on a group of criteria.The health care sector faces several types of problems,and one of the most important is selecting an appropriate supplier that fits the desired performance level.The development of service/product quality in health care facilities in a country will improve the quality of the life of its population.This paper proposes an integrated multi-attribute border approximation area comparison(MABAC)based on the best-worst method(BWM),plithogenic set,and rough numbers.BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency.For the treatment of uncertainty,a plithogenic set and rough number(RN)are used to improve the accuracy of results.Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness.Then,based on the plithogenic aggregation and the results of BWM evaluation,we use MABAC to find the optimal alternative according to defined criteria.To examine the proposed integrated algorithm,an empirical example is produced to select an optimal supplier within five options in the healthcare industry.

Improving Supply Chain Performance Through Supplier Selection and Order Allocation Problem

Suppliers play the vital role of ensuring the continuous supply of goods to themarket for businesses.If businesses do not maintain a strong bond with their suppliers,they may not be able to secure a steady supply of goods and products for their customers.As a result of failure to deliver products,the production and business activities of the business can be delayed which leads to the loss of customers.Normally,each trading enterprise will have a variety of commodity supply chains withmultiple suppliers.Suppliers play an important role and contribute to the value of the entire supply chain.Should any supplier encounters a problem,the whole supply chain of businesses will be affected and could lead to not guaranteeing the stable supply to the market.Thus,suppliers can be seen as a threat to businesses where they have the ability to increase input prices or decrease the quality of the required products and services they provide.The quantity of the business,and the supply lead time directly affect the operations and reduce the profitability of the business.The paper mainly focuses on the supplier selection problemunder a variety of price level and product families when using a two-phase fuzzy multi-objective linear programming.The objectives of the proposed model are to minimize the total purchasing and ordering cost in order to reduce the quantity of defective materials and the late-delivery components from suppliers.Moreover,the piecewise linear membership function is applied in themodel to determine an optimal solution which is based on the requirement of decision makers under their fuzzy environment.The results of this study can be applied in various business environment and provide a reliable decision tool for choosing potential suppliers relating to these objectives.Based on the results,the company canmake a good decision on supplier selection;therefore,the company can improve the quality and quantity of their final product.This is because,the best supplier can supply raw material using just-in-time application and reduce production risk on the manufacturing process.

China Procurement-Leveraging Supplier Selection and Supplier Management for Success

Successful China pro- curement is the result of a comprehensive set of complex and high-ly-specialized processes. Dis- tilling this down to a ＂magical recipe＂ for success is no simple task, and there are no shortcuts. However, as a useful reference, two fundamental ingredients for procurement success are： the selection of the right suppliers： and the effective management of chosen suppliers to optimize their performance.

A Model for Selecting a Biomass Furnace Supplier Based on Qualitative and Quantitative Factors

In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vietnam.Vietnam has favorable natural conditions for this energy production.Because it is hot and humid,and it has much rainfall and fertile soil,biomass develops very quickly.Therefore,byproducts from agriculture and forestry are abundant and continuously increasing.However,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta region.Biomass energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable development.Taking advantage of this energy source provides energy for economic development and ensures environmental protection.Due to the abovementioned favorable conditions,many biomass energy plants are being built in Vietnam.Like other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria decisions.In this case,decisionmakers must evaluate many qualitative and quantitative factors.These factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making environment.Therefore,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a Fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative factors.Furthermore,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-makers in other fields can use to find the best supplier.

Fuzzy Multi-criteria Decision Making for Decision Support in Port Capacity Upgrade

In many port capacity upgrade projects,choosing a supplier of equipment is a complicated decision,project managers must consider many criteria to choose a supplier to ensure the project is completed on time,optimal in terms of benefit and cost.Therefore,selecting the equipment supplier in this project is a multi-criteria decision-making process.The multicriteria decision-making(MCDM)model is applied in many fields to select the optimal solution,but there are very few studies using the MCDM model to support project managers in evaluating and selecting optimal solutions in port capacity upgrade project.In this research,the authors combine Fuzzy Analytic Network Process model and Weighted Aggregated Sum Product Assessment concepts to develop a decision support system in port capacity upgrade project.The scientific and practical contribution of this study is to successfully propose a decision support model in a fuzzy environment.The results of the study will be a useful guideline to assist decision makers in port capacity upgrading projects in Taiwan as well as in other countries around the world.

On some new fuzzy entropy measure of Pythagorean fuzzy sets for decision-making based on an extended TOPSIS approach

Fuzzy entropy measures are valuable tools in decision-making when dealing with uncertain or imprecise information.There exist many entropy measures for Pythagorean Fuzzy Sets(PFS)in the literature that fail to deal with the problem of providing reasonable or consistent results to the decision-makers.To deal with the shortcomings of the existing measures,this paper proposes a robust fuzzy entropy measure for PFS to facilitate decision-making under uncertainty.The usefulness of the measure is illustrated through an illustration of decision-making in a supplier selection problem and compared with existing fuzzy entropy measures.The Technique for Order Performance by Similarity to Ideal Solution(TOPSIS)approach is also explored to solve the decision-making problem.The results demonstrate that the proposed measure can effectively capture the degree of uncertainty in the decision-making process,leading to more accurate decision outcomes by providing a reliable and robust ranking of alternatives.

A decision support model for supplier portfolio selection in the retail industry

In this paper we propose and test a staged knapsack model to create a supplier portfolio for retailers.The first two stages in the model use judgement criteria related to supplier characteristics and supplier fit,gathered from managers to create a portfolio that optimizes supplier rank and fit scores.In the third stage we optimize cost by considering landed costs for each supplier in the portfolio to arrive at the final set of suppliers.The results indicate that the criteria used,and the staged refinement of the supplier pool resulted in a better fit than just considering the landed costs of the final pool of suppliers without rank and fit score constraints.The proposed method will enable purchasing managers to strategically create a supplier portfolio that will suit the retailer’s needs more effectively.

Multi-criteria decision making method based on improved cosine similarity measure with interval neutrosophic sets

Purpose–The fuzziness and complexity of evaluation information are common phenomenon in practical decision-making problem,interval neutrosophic sets(INSs)is a power tool to deal with ambiguous information.Similarity measure plays an important role in judging the degree between ideal and each alternative in decision-making process,the purpose of this paper is to establish a multi-criteria decision-making method based on similarity measure under INSs.Design/methodology/approach–Based on an extension of existing cosine similarity,this paper first introduces an improved cosine similarity measure between interval neutosophic numbers,which considers the degrees of the truth membership,the indeterminacy membership and the falsity membership of the evaluation values.And then a multi-criteria decision-making method is established based on the improved cosine similarity measure,in which the ordered weighted averaging(OWA)is adopted to aggregate the neutrosophic information related to each alternative.Finally,an example on supplier selection is given to illustrate the feasibility and practicality of the presented decision-making method.Findings–In the whole process of research and practice,it was realized that the application field of the proposed similarity measure theory still should be expanded,and the development of interval number theory is one of further research direction.Originality/value–The main contributions of this paper are as follows:this study presents an improved cosine similarity measure under INSs,in which the weights of the three independent components of an interval number are taken into account;OWA are adopted to aggregate the neutrosophic information related to each alternative;and a multi-criteria decision-making method using the proposed similarity is developed under INSs.