Designing a Log-Logistic-Based EWMA Control Chart Using MOPSO and VIKOR Approaches for Monitoring Cardiac Surgery Performance

Authors

DOI:

https://doi.org/10.31181/dmame712024903

Keywords:

Exponentially weighted moving average, Risk-adjustment, Accelerated failure time, Multi-objective particle swarm optimization, PSO, VIekriterijumsko KOmpromisno Rangiranje, VIKOR

Abstract

This study aims to develop a risk-adjusted Exponentially Weighted Moving Average (EWMA) control chart for computer-based performance monitoring in cardiac surgery. Patients have distinct risk factors that impact the surgical process before it even begins. As a result, risk adjustment is carried out utilizing the Accelerated Failure Time (AFT) model to consider these factors. Before using the risk-adjusted EWMA chart, the optimal parameter design should be established, considering the required statistical and economic factors. A model for Multi-Objective Decision Making (MODM) with multiple assignable causes has been proposed to accomplish this. The model is solved using a two-stage methodology based on the Multi-Objective Particle Swarm Optimization (MOPSO) method and the VIekriterijumsko KOmpromisno Rangiranje (VIKOR) method. An actual case study for cardiovascular patients has been undertaken to demonstrate the performance and effectiveness of the suggested model. The multi-objective and pure economic models have been thoroughly compared. The economic model with statistical constraints and the multi-objective model have also been compared again. The findings suggest that the multi-objective design of the risk-adjusted EWMA chart exhibits higher statistical performance in both cases against a small augment in cost.

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Published

2024-01-01

How to Cite

Nasiri Pour, A., Azizi, A., Rahimzadeh, A., Ershadi, M. J., & Zeinalnezhad, M. (2024). Designing a Log-Logistic-Based EWMA Control Chart Using MOPSO and VIKOR Approaches for Monitoring Cardiac Surgery Performance . Decision Making: Applications in Management and Engineering, 7(1), 342–363. https://doi.org/10.31181/dmame712024903

Issue

Vol. 7 No. 1 (2024): Decision Making: Applications in Management and Engineering

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Regular articles

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