Game theory
Elham Sadat Mousavi; Ashkan Hafezalkotob; Ahmad Makui; Mohammad Kazem Sayadi
Abstract
This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader ...
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This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader and the hotels as the followers of the Stalkberg model, then apply the Nash equilibrium to determine the optimal price and demand of hotels in competitive conditions, taking into account the discount. By considering a government utility function, the optimal level of government tariffs is determined. The results indicate that government intervention in the tourism industry includes measures that benefit tourism. Because the government can increase the hotel revenue and expand tourism in favor of hoteliers by reducing its profits. Extensive analysis has been performed on five-star, four-star, and three-star hotels in a tourist area in Iran, and some of the most important managerial insights have been explained.
Operations Research
Elham Samadpour; Rouzbeh Ghousi; Ahmad Makui; Mehdi Heydari
Abstract
In Home Health Care (HHC) operations, one of the major aims of HHC centers is to timely meet patients' demands. According to the feedback from HHC centers, their decision-makers deal with some complexity in scheduling and routing of their health workers. Inspired by this point, the present research introduces ...
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In Home Health Care (HHC) operations, one of the major aims of HHC centers is to timely meet patients' demands. According to the feedback from HHC centers, their decision-makers deal with some complexity in scheduling and routing of their health workers. Inspired by this point, the present research introduces a new HHC routing and scheduling problem considering different skill levels of health workers and different levels of patients’ needs. So, in such a condition, a highly qualified health worker can visit those patients who need lower-skilled demands while a low-qualified health worker cannot visit those who request higher skills. In this way, the total cost of the system will be lower compared to the situation in which the patients' needs exactly match the health workers' skills. Moreover, we consider that the maximum number of homes each health worker is tasked to visit during the day is specified and if more patients than this specified limit are assigned to each health worker, an additional cost will be imposed on the center in proportion to the excess number of patients. Since patient satisfaction, which is obtained with timely visits, is important for each HHC center, a hard time window is considered for each patient. The presented model is solved using the GAMS software with the CPLEX solver. Along with the MIP approach, a metaheuristic algorithm based on a Simulated Annealing (SA) algorithm is adopted to solve the problem. The results give the managers insight into this method of cost management in comparison with manual and traditional traditional planning. This study may help the decision-makers of HHC centers make more accurate decisions which, in turn, result in timelier service provision, increase the patients' satisfaction level, and improve the overall efficiency of HHC centers.
Aahmad Makui; Farzaneh Ashouri; Farnaz Barzinpour
Abstract
In this paper, we introduce a two stages model for allocation of injuries and medical supplies to medical centers. In the first stage a multi objective mathematical model allocates injured people from the affected neighborhood to medical centers. In the second stage a single objective linear model allocates ...
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In this paper, we introduce a two stages model for allocation of injuries and medical supplies to medical centers. In the first stage a multi objective mathematical model allocates injured people from the affected neighborhood to medical centers. In the second stage a single objective linear model allocates medical supplies from the supply points to medical centers. The first stage’s objective is simultaneously minimizing the total relief time and costs and maximizing the level of matching the type of injury with the specialized field of the medical centers those injuries are sent. The second stage’s objective is to minimize the costs of allocating medical supplies to medical centers. An integrated model that combines the two previous models is presented and comparing the results with the two stages model. Proposed models are applied to one of the districts of Tehran to demonstrate their effectiveness. The case study includes two affected neighborhood and four medical centers and three supply points. ϵ-constraint method is used to produce the Pareto optimal solutions in a MOMP.