فهرست مطالب

  • Volume:7 Issue: 2, 2020
  • تاریخ انتشار: 1399/06/10
  • تعداد عناوین: 5
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  • Nazila Adabavazeh, Mehrdad Nikbakht *, Alireza Amirteimoori Pages 1-35
    Communities are constantly seeking to manage the damages which are caused by crises. In this regard, health centers have become the most expensive unit of the health system as they provide quick and timely health care services to reduce the effects of unexpected accidents. So, their planning and preparation should be considered as an important part of strategic health policies. The purpose of this study is to investigate performance evaluation techniques for health units, which is helpful for WHO to identify the capabilities of crisis management and the limitations of world health units. This study evaluates the performance of the world health systems dealing with Corona-virus based on parametric and nonparametric statistical techniques according to "Population, GPD Per Capita, Total Recovered, Total Cases, and Total Deaths". This descriptive cross-sectional study is performed on the World Population Review, Worldometer, WHO data of Covid-19 from 1 March -11 April 2020. Based on the results, the efficient and inefficient health system units are identified. The results of this study show that 52 medical centers have not performed efficiently. The average efficiency of inefficient units is 0.30. On this basis, most of the studied countries do not operate efficiently due to the lack of optimal use of resources. Ineffective health system units call for greater attention of WHO in promoting health culture during the crisis management of common viruses. Therefore, there is a capacity to improve efficiency by 70%. By conducting this research, in addition to the introduction of functional patterns to the top health managers, it is possible to plan more accurately to develop the capacity of health care services and save resources.
    Keywords: health system unit, Coronavirus, DEA, COVID-19, WHO
  • Mostafa Zaree, Reza Kamranrad *, Mojtaba Zaree, Iman Emami Pages 36-55

    Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources .Therefore, managing and scheduling a project is a necessity for the project.The timing of a project is to specify a sequence of times for a series of related activities.According to their priority and their latency, so that between the time the project is completed and the total cost is balanced.Given the balance between time and cost, and to achieve these goals, there are several options that should be considered among existing options and ultimately the best option to perform activities to complete the project.In this research, a mathematical model of project scheduling with multiple goals based on cost patterns and consideration of resource constraints is presented, and this problem is considered as a problem for NP-hard issues in family hybrid optimization. GA,PSO and SA Meta-heuristic algorithmsareused to solve the proposed model in project scheduling and the results are compared with each other.

    Keywords: Project scheduling, NPV maximizing, payment patterns, Resource constraints, meta-heuristic algorithms
  • Mansooreh Iravani, Reza Bashirzadeh *, M. J. Tarokh Pages 56-76
    This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability by considering to minimize the air pollution and maximize the social welfare as its objectives. This model determines optimal prices (bus fare and car toll) and optimal bus frequency simultaneously in an integrated model. The model is based on discrete choice theory and consideres the modes’ utility functions in its formulation. The proposed model is solved by two meta-heuristic methods (Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Multi-Objectives Harmony Search (MOHS)) and the numerical results of a case study in Tehran are presented. The main managerial insights resulted from this case study is that its results support the idea of “free public transportation” or subsidizing the public transport as an effective way to decrease the transport related air pollution
    Keywords: Bi-objective Optimization, public transportation pricing, Air pollution, NSGA-II, MOHS
  • Masoud Rabbani *, Amin Abazari, Hamed Farrokhi Asl Pages 77-97

    Using second-generation biomass and biofuel deal with environmental pollution and CO2 emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO2 emissions. The economic analysis consists of three scenarios for supplying biomass. The SVM method specifies the potential place to build the bio-refinery. The next step solves the model with the augmented ε-constraint method. Finally, results show that biomass production and imports simultaneously reduce costs by 24.5% compared to the production scenario and 4.3% compared to the import scenario. According to the results obtained, despite the increase in cost, it reduces the amount of CO2 emissions. So, the Pareto solution resulted from the augmented ε-constraint method for the problem is determined as one of the most effective techniques to help the decision-makers.

    Keywords: bio-refinery, Biomass, SVM, economical analysis, CO2 emission
  • Milad Hematian *, Mirmehdi Seyyedesfahani, Iraj Mahdavi, Nezam Mahdavi Amiri, Javad Rezaeian Pages 98-118
    One of the most important aspects of human resource management is the allocation of the workforce to activities. Human resource assignment to project activities for its scheduling is one of the most real and common issues in project management and scheduling. This becomes even more significant when human resource assignment to multiple projects simultaneously is considered. On the one hand, workforces can have multi skills due to technological and scientific development so that they can be assigned to project activities based on their skill level. On the other hand, the learning effect is also taken into account to make the model more realistic. These factors can affect completion time, total cost and execution quality of projects. In this study, a multi-objective optimization model for multi-project scheduling and multi-skilled human resource assignment problem based on the learning effect and activities' quality is presented. A mixed-integer linear programming model (MILP) is developed for the proposed problem and solved by the ε-constraint method in GAMS software. Managers can select a solution based on their priority. Finally, a sensitivity analysis is done on the learning and forgetting effect to investigate their impacts on each objective function.
    Keywords: Multi-Objective Optimization, Multi-project scheduling, multi-skilled human resources, learning, forgetting effect, activity's quality level