Multi-criteria Decision Making Based on PROMETHEE Method

Sun, Zhe; Han, Min

doi:10.1109/ccie.2010.110

Cited by 32 publications

(15 citation statements)

References 4 publications

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“…This is a structured method for preferential ranking. Patients' prioritization was conducted considering survivability (positive criteria) and the length of hospitalization (negative criteria) as well as definitions of indifference and preference threshold, shape of the function, the weight of criteria, and data associated with choices (27).…”

Section: Methodsmentioning

confidence: 99%

Neurocritical Care Unit Bed Allocation: Optimization Based on Prioritization Using Simulation

et al. 2018

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Background: Neurological trauma and diseases are the second cause of mortality and the main reason of acquired disability. Neurocritical care plays a major role in treating such patients. A longer life expectancy, treatment of incurable diseases, and limited resources available to add to hospital beds necessitates engineering the knowledge of health systems to prioritize allocation of current resources and present a proper pattern.Objectives: The current study aimed at optimizing bed use and shortening the length of patients' hospitalization in neurocritical care unit (NCCU) of Loghman Hakim hospital affiliated to Shahid Beheshti University of Medical Sciences, Tehran, Iran, and completely stimulating the procedure of bed allocation and prioritization of patients.Methods: Data of 420 patients hospitalized in NCCU was gathered and the procedure of bed allocation simulation was performed considering the priorities defined based on the length of hospitalization and patients' chance of survival. The PROMETHEE (preference ranking organization method for enrichment evaluation) method was used to prioritize and allocate beds. To study the consequences of the suggested method, event discrete simulation tool was used to compare the current status and the results of the new method for 20 periods each including one month data. Results:The mean number of patients admitted to NCCU during one month without any prioritization was 76, while it increased to 86 based on prioritization. Conclusions:Patients' simulation and prioritization using the PROMETHEE method resulted in 13% rise in the number of patients admitted to NCCU and higher utilization of this ward.

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Section: Methodsmentioning

confidence: 99%

Neurocritical Care Unit Bed Allocation: Optimization Based on Prioritization Using Simulation

et al. 2018

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“…More a visible risk sources the more its detection probability (Blackhurst et al, 2005). Zhaoxu and Min (2010) have reported that linear preference function has been most widely used for practical application. In this work, linear preference function is used for all the criteria with threshold values as described below.…”

Section: Compute the Rpn And Construct The Promethee Evaluation Matrixmentioning

confidence: 98%

Supply chain risk prioritisation using a hybrid AHP and PROMETHEE approach

Venkatesan

Kumanan

2012

IJSOM

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Supply chain is a network of facilities designed to procure, produce, and distribute goods to customers at right quantities, to the right locations and at the right time. Supply chain studies are focused for improving the operational efficiency through cost reduction. In recent years, supply chains have become increasingly vulnerable to risks resulting in poor financial performance and customer service. Managing the supply chain risks is a challenging task. Resilience and responsiveness-based strategies are being attempted to build a robust supply chain. To select and evaluate the appropriate mitigation strategies, supply chain risks are to be prioritised. Supply chain risk prioritisation is a multi criteria decision making (MCDM) problem. Developing the MCDM models for supply chain risk prioritisation need attention. In this research a hybrid analytic hierarch process (AHP) and preference ranking organisation method for enrichment evaluation (PROMETHEE) approach is proposed for supply chain risk prioritisation. A case example of a typical plastic industry is presented to illustrate the performance of the proposed approach.

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“…Considering the test case generation with respect to multi objective optimization PARETO [24] solutions and multicriteria decision-aid technique is applied to select the finest solution. PROMETHEE technique [25] of decision is applied such that ranking amongst the individuals. Positive ranking is given as in Eq.…”

Section: A Genetic Algorithmmentioning

confidence: 99%

Integrated Pairwise Testing based Genetic Algorithm for Test Optimization

Swathi¹,

Tiwari²

2021

IJACSA

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Generation of Test cases in software testing is an important and a complex activity as it deals with diversified range of inputs. Fundamentally, test case generation is considered to be a multi-objective problem as it aims to cover many targets. Deriving test cases for the Web Applications has become critical to the most of the enterprises. In this paper, a solution for generating test cases for web applications is proposed; the solution uses the System Graph (consisting of links and data dependencies) considering that test cases were based on a combination of input values and data dependencies. Pairwise testing is used to derive the test cases to be executing from entire test cases and then a genetic algorithm is proposed to generate test cases specific to functional testing. The proposed approach was tested through two distinct experiments by measuring the code coverage at every generation and results show that genetic algorithm used increased the fitness value and code coverage. Overall, the results of the paper validate the proposed approach and algorithm, having potential in further construct an automated integrated solution for generating test cases for the entire process.

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Multi-criteria Decision Making Based on PROMETHEE Method

Cited by 32 publications

References 4 publications

Neurocritical Care Unit Bed Allocation: Optimization Based on Prioritization Using Simulation

Neurocritical Care Unit Bed Allocation: Optimization Based on Prioritization Using Simulation

Supply chain risk prioritisation using a hybrid AHP and PROMETHEE approach

Integrated Pairwise Testing based Genetic Algorithm for Test Optimization

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