Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks

Lima, Francisco Rodrigues; Carpinetti, Luiz César Ribeiro

doi:10.1016/j.ijpe.2019.02.001

Cited by 86 publications

(39 citation statements)

References 46 publications

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“…The performance attributes of SCOR data are shown below [11]. The SCOR's process includes: definition of process components, input-output, process performance data, selected best supplier [8,[12][13][14][15]. SCOR uses historical supply chain data to see how it works and develops, which defines the five general performance attributes and three measurement levels that analysts offer [13,15].…”

Section: Maintenance Cost Transportation Costsmentioning

confidence: 99%

“…However, there are still many shortcomings that ANP method has not solved, such as problems with uncertainty when performing matrix comparison matrix [27,29]. Dividing the decision problem into subproblems, the pairs of comparisons increase the number creating disadvantages in the evaluation process [15]. The traditional ANP method is incomplete because it has not yet shown data clearly to produce accurate results [27,29,30].…”

Section: Maintenance Cost Transportation Costsmentioning

confidence: 99%

“…The problem of decision-making becomes more complicated when there are many groups of people and experts involved in the decision-making process. In order to select suppliers with objectivity, Ability to meet delivery demand [8,[10][11][12][14][15][16]20] Ability to receive returns products Ability to produce new raw materials Costs Material cost [8,[11][12][13][14]16,19]…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry

Wang,

Nguyen,

Chyou

et al. 2019

Mathematics

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To be able to compete in the domestic plastic industry, small and medium-sized enterprises producing plastic need to proactively find the supply of raw materials, avoiding shortages like in the previous years. Purchasing is extremely important and will create a competitive advantage with competitors in the market, so finding suppliers will determine the success in the later stages of the production chain. With the development of the current information system, selection and evaluation have become important in order to achieve effective decision-making through optimal options. In this study, the authors provide a new approach for decision-makers in evaluating and selecting suppliers, which is formulated based on the supply chain operation reference (SCOR) model, fuzzy analytic network process (FANP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The contribution of this research is to propose a multicriteria decision-making model (MCDM) for raw material supplier selection in the plastic industry. This research also provided a useful guideline for supplier selection in other industry.Mathematics 2019, 7, 981 2 of 17 avoiding subjective factors such as human factors, documents, relationships, etc., that is vague and incomplete in making decisions is crucial [4]. Moreover, most previous studies have assumed that each criterion cluster in the method they use has equal weight to solve the problem with a weighted hyper matrix [5,6]. Therefore, previous studies have not exploited the advantages and disadvantages of the models or methods they have applied. With the development of the current information system, selection and evaluation have become important to achieve effective decision-making through optimal options [7].According to the Vietnam Plastics Association (VPA), each year, Vietnam's plastic industry needs about 5 million tons of plastic materials and hundreds of additives, while domestic production can only supply about 900,000 tons of raw materials/year. According to the data from the General Department of Customs, Vietnam must import 4.54 million tons of plastic materials worth nearly $6.3 billion, up 15.7% over the same period.The reliance on imported plastic materials not only causes businesses to stagnate capital because of stockpiling raw materials, but also has potential risks on exchange rates and world oil prices. Every time the VND/USD exchange rate increases, input costs of plastic businesses will increase accordingly.The primary goal of this research is to propose a multi criteria decision-making model (MCDM) for raw material supplier selection in plastic industry and also provide a useful guideline for supplier selection in other industry.In this study, the proposed model provides a new approach for decision-makers in evaluating and selecting suppliers, which is formulated based on the supply chain operation reference (SCOR) model, fuzzy analytic network process (FANP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).This paper provides research background, moti...

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Section: Maintenance Cost Transportation Costsmentioning

confidence: 99%

Section: Maintenance Cost Transportation Costsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry

Wang,

Nguyen,

Chyou

et al. 2019

Mathematics

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“…In order to function the NN, the weights are being initialized. As a result, the network is made to learn by using some learning methods and rules [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. The connection weights are adjusted during the training.…”

Section: Introductionmentioning

confidence: 99%

An efficient learning algorithm for periodic perceptron to test XOR function and parity problem

et al. 2020

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Artificial neural network (ANN) is an important tool, which is used in numerous fields, such as computer vision, pattern recognition, signal processing, solving optimization problems, and voice analysis and synthesis. Many real-life problems, where the future events play a vital role, are based on the past history. For example, predicting the behavior of stock market indices and electrical load forecasting. In this paper, we establish an efficient learning algorithm for periodic perceptron (PP) in order to test in realistic problems, such as the XOR function and the parity problem. Here, the periodic threshold output function guarantees the convergence of the learning algorithm for the multilayer perceptron. By using the binary Boolean function and the PP in single and multilayer perceptron, XOR problem is solved. The performance of PP is compared with multilayer perceptron and the result shows superiority of PP over the multilayer perceptron.

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“…The researcher examined a number of previous studies relevant to the background of this research. The study was obtained from the study of [1][2][3][4][5][6][7][8][9][10][11]. This was done to strengthen the phenomenon in this study.…”

Section: Introductionmentioning

confidence: 99%

Building Framework of Supply Chain Vanilla Commodity in Indonesia: Approach with SCOR 12.0

Boxy¹,

Permana²,

Wuryandari³

2020

Proceedings of the 4th International Conference on Management, Economics and Business (ICMEB 2019)

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Vanilla commodities are food needs needed for complementary mixtures of food needs, so the stability of the vanilla food supply chain needs to be well developed in maintaining sustainable needs. The measurement study of this research is the organization of the Perhimpunan Petani Vanili Indonesia (PPVI) where the organization aims to develop and improve supply chains for farmer groups incorporated in organizations throughout Indonesia. The improvement in the performance of the supply chain organization focuses on the SCOR 12.0 approach and is processed through the analytical hierarchy process (AHP) with the development of KPIs in supply chain performance attributes. The results of the analysis show that the attributes of reliability, agility, and cost have the lowest valuation so that further development and identification is needed in improving the performance of the supply chain. The discussion and further implications of this research are designing lean agriculture development, improving quality management and developing operational, technical cost structures in the supply chain objects.

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Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks

Cited by 86 publications

References 46 publications

Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry

Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry

An efficient learning algorithm for periodic perceptron to test XOR function and parity problem

Building Framework of Supply Chain Vanilla Commodity in Indonesia: Approach with SCOR 12.0

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