Intelligent Decision-Making Algorithm for Supplier Evaluation Based on Multi-criteria Preferences

Jemmali, Mahdi; Alharbi, Mafawez; Melhim, Loai Kayed B.

doi:10.1109/cais.2018.8441992

Cited by 13 publications

(12 citation statements)

References 16 publications

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“…Multicriteria decision support system (MCDSS) is used to facilitate the issues arise from daily life. Due to the usefulness of multicriteria based decision support system, researchers are trying to devise machine learning algorithms to provide an intelligent decision making alternative [27][28][29]. Decision support systems (DSS) are used in a variety of applications and domains for solving or assisting the decision maker to take a more appropriate decision, and these can be exploited in almost all domains to solve decision problems, such as DSS in Agriculture [30], energy sector [31], waste management, and business [32], [33].…”

Section: Anp Approach For the Selection Of Elicitation Techniquementioning

confidence: 99%

Attributes-Based Decision Making for Selection of Requirement Elicitation Techniques Using the Analytic Network Process

Ullah

et al. 2020

Mathematical Problems in Engineering

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Requirement engineering is the first phase of software engineering. In requirement engineering, the first phase is requirement elicitation (RE), which is the most critical and error-prone activity. In this phase, the requirements are extracted from various sources; after extraction, they are analyzed and documented for a specific purpose of software development. In RE, process requirements from stakeholders are gathered, upon which the entire software product failure and success are dependent. In order to accomplish the goal of requirement elicitation, various techniques are used. However, the selection of these techniques is a very challenging task, as one technique may suit a situation but may not be suited for other situations. Besides this, project attributes such as documentation culture of organization, degree of relationship among stakeholders, and familiarity to domain also have a great impact on the process of technique selection. The reason is that there is no empirical value of the techniques that provide help in techniques selection to analyze the basis software project attributes. This study proposed the analytic network process, which is one of the multicriteria decision making processes for the elicitation technique selection process with respect to criterion attributes of project. The motivation toward the use of the ANP approach for the selection of requirement selection technique is that there are dependencies existing among attributes of the project elements. So, the ANP approach is capable of dealing with such situations where dependencies and complexity occur. Results of the proposed study demonstrate that the technique helps in complex situations where decision making is difficult based on the alternatives.

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Section: Anp Approach For the Selection Of Elicitation Techniquementioning

confidence: 99%

Attributes-Based Decision Making for Selection of Requirement Elicitation Techniques Using the Analytic Network Process

Ullah

et al. 2020

Mathematical Problems in Engineering

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“…Many research types have been performed in the field of supplier selection and evaluation, such as: adopting different approaches with different implementations and employing a lot of applied mathematics and methodologies [3]. Different researches resulted in many decision support tools that are based on multi-criteria, which is been presented as a decisions supporting tools [4], [5], [6] and [7].…”

Section: Related Workmentioning

confidence: 99%

“…The presented approaches were analyzed to find the limitations by a critical study of the given approaches and then to determine which is the most widely used and adopted approaches in the supplier evaluation and selection problem. recently, authors in [7] presented an intelligent DM P A model based on a set of multi-criteria preferences that can be adopted by decision makers, in supply chain management and e-procurement processes, to select the appropriate offer among the presented offers from many suppliers.…”

Section: Related Workmentioning

confidence: 99%

Multi-criteria Intelligent Algorithm for Supply Chain Management

Jemmali¹,

Melhim²,

Alharbi³

2019

IJACSA

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In most societies, supply chain management and e-procurement processes, are one of the cornerstones of any economy and a primary influencer on people's lives. Providing these communities with their different commodity needs depends on a wide range of suppliers. Due to supplier's variety and diversity; the process of choosing the suitable supplier is considered the difficult and critical process, especially if this process is performed traditionally then decision making will be time and effort consuming to reach the desired results. To solve the problem of choosing the suitable supplier, this research suggests an intelligent algorithm, based on a given determinants that are specified by the decision maker or the customer. The proposed algorithm employs a set of intelligent formulas that will convert the predefined preferences into quantitative measurements. Quantitative measurements will be used to differentiate between different suppliers or between the set of given offers. The experimental results showed that D3S model employed the given preferences and succeeded in selecting the most appropriate offer among the many presented offers by the available suppliers.

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“…Recent methodologies and approaches on the way to solving issues of the increase of data into diverse natures including value, volume, variety, velocity, and veracity, extracting significant information are challenging issues, DSS is furnished with the control of MCDSS for supporting the decisions maker in right decision in complex situations. Based on the success of MCDSS, practitioners and researcher are endeavouring to incorporate the control of intelligent decision-making for the available alternative [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

A Review on Multicriteria Decision Support System and Industrial Internet of Things for Source Code Transformation

Qinxia

Nazir

Gao

et al. 2021

Scientific Programming

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The large scale increase of communication and number of devices in the Industrial Internet of Things (IIoT) has rapidly enabled practitioners to make decisions based on multicriteria. Multicriteria decision support systems (MCDSSs) play an important role in decision-making for a particular situation based on several criteria. Making of decision based on multicriteria is the main issues for research community and practitioners of the IIoT. Several decision support systems (DSSs) are offered for making decisions which have the potentiality to support the activities of the decision-making process. The suggested study shows a review on the existing decision support systems for the IIoT for source code transformation which will enable research community and practitioners of the industry to use the existing methods, tools, approaches, and techniques and to provide novel solutions for the smooth industry of Internet of Things.

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Intelligent Decision-Making Algorithm for Supplier Evaluation Based on Multi-criteria Preferences

Cited by 13 publications

References 16 publications

Attributes-Based Decision Making for Selection of Requirement Elicitation Techniques Using the Analytic Network Process

Attributes-Based Decision Making for Selection of Requirement Elicitation Techniques Using the Analytic Network Process

Multi-criteria Intelligent Algorithm for Supply Chain Management

A Review on Multicriteria Decision Support System and Industrial Internet of Things for Source Code Transformation

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