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.
Alireza Rashidi Komijan; Amin Gordani
Abstract
The problem of Airline planning has totally been divided into four sub-problems.These problems include Flight Scheduling, Fleet Assignment, Aircraft Routing, Maintenance, and Crew Scheduling. In this research, firstly, we defined basic concepts and common terminology about Airline Planning then early ...
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The problem of Airline planning has totally been divided into four sub-problems.These problems include Flight Scheduling, Fleet Assignment, Aircraft Routing, Maintenance, and Crew Scheduling. In this research, firstly, we defined basic concepts and common terminology about Airline Planning then early models and previous researchers were presenting investigated articles. Moreover, by identifying existing research gaps, an Integrated Mathematical model presented for Aircraft Routing and Crew Scheduling for Airlines with Multi Fleet and Multi Maintenance hub with considering the rules of the Airlines. The main purpose of the proposed model is to determine the flight chains for each aircraft and crew assignments to all aircrafts with the attention to the airlines rules and regulations for aircrafts and crew. In the integrated models by previous researcher in this field, usually the type of fleet is considered the same while in the model presented in this research, the type of fleet is considered different. Other innovations of this research consider several maintenance units for an airline. In addition, the minimizations of deadheading flights for crew and aircraft that can impose heavy costs to the airline is presented as a part of the objective function in the model presented. Finally, the problem has been solved into small dimensions by GAMS software and in order to solve it in the larger dimensions a meta-heuristic method is being used, such as genetics algorithm. At the end, we have presented the results, which came from meta-heuristic Algorithm and GAMS Software.
