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        1 - The Optimal Number of Hospital Beds Under Uncertainty: A Costs Management Approach
        Saeed Khalili Mohammad Ghodoosi Javad Hasanpour
        Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of More
        Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of beds in hospitals leads to patients’ admission loss and consecutively profit loss. On the other hand, increasing the bed count leads to an increase in equipment expenses. Therefore, in order to determine optimal bed capacity, it is of utmost importance to consider these two costs simultaneously. In our paper, hospital admission system is modeled with a multi-server queuing system (M/M/K). Therefore, to calculate the total cost function, limiting probabilities of multi-server queueing model is used. Furthermore, due to uncertain nature of parameters, such as interest rate and hospitalization profit in various future time periods, these uncertainties are covered by fuzzy logic. Finally, to determine the optimal bed count, Lee and Li''''s fuzzy ranking method is used. This model is implemented ona case study. Its goal is to determine the optimal bed count for emergency unit of Razi hospital in Torbat Heydarieh. Considering the high capability of Markovian chains in modeling different circumstances and the various queueing models, the proposed model can be extended for various hospital units. Manuscript profile
      • Open Access Article

        2 - Optimizing a bi-objective preemptive multi-mode resource constrained project scheduling problem: NSGA-II and MOICA algorithms
        Javad Hasanpour Mohammad Ghodoosi Zahra Sadat Hosseini
        The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary wi More
        The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategies. We also introduce the preemptive extension of the problem which allows activity splitting. In this paper the preemption multi-mode resource-constrained project scheduling problem (P-MMRCPSP) with Minimum makespan and the maximization of net present value (NPV) has been considered. Since the considered model is NP-Hard, The performance of our proposed model is evaluated by comparison with two well-known algorithms; non-dominated sorting genetic algorithm (NSGA II), multi-objective imperialist competitive algorithm (MOICA). These metaheuristics have been compared on the basis of a computational experiment performed on a set of instances obtained from standard test problems constructed by the ProGen project generator, where, additionally, cash flows were generated randomly with the uniform distribution. Since the effectiveness of most meta-heuristic algorithms significantly depends on choosing the proper parameters. A Taguchi experimental design method (DOE) was applied to set and estimate the proper values of GAs parameters for improving their performances. The computational results show that the proposed MOICA outperforms the NSGA-II. Manuscript profile