uncertainty
Hossein Firouzi; Javad Rezaeian; Mohammad Mehdi Movahedi; Alireza Rashidi Komijan
Abstract
A multi-objective mathematical model for the reverse supply chain of hospital waste management in Iran during the COVID 19 is presented in this paper considering the dimensions of sustainability. The objectives of the presented model are: 1) Minimizing the cost of building facilities and waste treatment ...
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A multi-objective mathematical model for the reverse supply chain of hospital waste management in Iran during the COVID 19 is presented in this paper considering the dimensions of sustainability. The objectives of the presented model are: 1) Minimizing the cost of building facilities and waste treatment at the centers, vehicle fuel costs and environmental costs due to emission pollutant; 2) Maximizing the energy generated by the waste combustion process; 3) Minimizing the risk of virus transmission due to poor waste management and 4) Maximizing the number of labor jobs in established centers. Noted that, the existing uncertainties are modeled by using fuzzy set theory. Due to the multi-objective nature of the model, two multi-objective algorithms namely Pareto archive based krill herd algorithm and Non-dominated Sorting Genetic Algorithm II (NSGA II) are used to solve the mentioned problem. The results show that the proposed krill herd algorithm converges to a solution with higher quality and dispersion than the NSGA-II. In addition, by comparing the spacing index and running time of the two algorithms, it’s found that the NSGA-II searches the space solution with higher uniformity and solves the model in less time.
Somayeh Kavianpour; Gavad Rezaeian
Abstract
Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on ...
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Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on job satisfaction and quality of received services. A linear mathematical model is proposed and since this problem is NP-hard, Genetic Algorithm is provided for solving the problem and finally Implemented in Imam Khomeini hospital of Noor city as a real sample. Computational results and performance of the proposed algorithm in terms of solution quality and computational time were analyzed. Accreditation standards for hospitals as well as the Productivity laws are used in the proposed model. Production of timetables by the proposed model, resulting in improved satisfaction levels of nurses and their job performance.
