Objectives: Cesarean delivery without medical indication has regularly increased among Iranian women in the last three decades, and Iran has one of the highest rates of cesarean in the world. The present study aimed at reviewing the studies regarding the increase of cesarean in Iran and discussing the root causes for such an increase. Methods: This literature review focused on the existing quantitative and qualitative studies conducted from January 1990 to January 2019 regarding the reasons for an increase in the cesarean section in Iran. The combination of keywords including "cesarean section", "C-section", "cesarean delivery", and "Iran" was searched in several databases such as MEDLINE/PubMed, Embase, ISI Web of Science and Scopus, along with national databases (e.g., SID, MagIran, Iran Medex, and IranDoc). Results: A dramatic rise in cesarean birth stems from a number of factors including the role of health care professionals, insurance companies, socio-cultural factors, and the health policies, all of which have their roots in the medicalization of birth. Conclusions: In general, reducing the cesarean on maternal request necessitates the de-medicalization of birth, cultural awareness through the mass media, informing women of the long-term complications of cesarean, and physical and mental preparation of the mother. In addition, other contributing factors include encouraging inter-professional teamwork and collaboration between midwives and obstetrician-gynecologists, transforming the current curriculum of the midwifery and residency education, applying the midwifery-led care models, and decreasing the fear of litigation in midwifery and obstetrics-gynecology. Otherwise, maternal and fetal mortality will rise in the near future due to increased complications in subsequent pregnancies.
Production scheduling and reliability of machinery are prominent issues in flexible manufacturing systems that are led to decreasing of production costs and increasing of system efficiency. In this paper, multiobjective optimization of stochastic failureprone job shop scheduling problem is sought wherein that job processing time seems to be controllable. It endeavours to determine the best sequence of jobs, optimal production rate, and optimum preventive maintenance period for simultaneous optimization of three criteria of sum of earliness and tardiness, system reliability, and energy consumption. First, a new mixed integer programming model is proposed to formulate the problem. Then, by combining of simulation and NSGA-II algorithm, a new algorithm is put forward for solving the problem. A set of Pareto optimal solutions is achieved through this algorithm. The stochastic failure-prone job shop with controllable processing times has not been investigated in the earlier research, and for the first time, a new hedging point policy is presented. The computational results reveal that the proposed metaheuristic algorithm converges into optimal or near-optimal solution. To end, results and managerial insights for the problem are presented. KEYWORDScontrollable processing times, failure-prone manufacturing system, modified hedging point policy, Pareto optimal solutions, stochastic job shop scheduling | INTRODUCTIONFailure-prone manufacturing systems (FPMSs) can be defined as a subcategory of flexible systems with stochastic breakdown and maintenance of machines. Indeed, the major goal is to identify the production rate; accordingly, holding, shortage, and maintenance costs could be reduced in a long-run planning horizon. FPMSs are models for studying manufacturing systems considering system ambiguities. Buffers in manufacturing systems play the role of decreased impact of machine breakdown on meeting demand. Thus, it seems indispensable to identify the optimal level of buffers to reduce holding and shortage costs. Seeing as machines in flexible manufacturing systems can produce with various speeds, identifying the optimal speed is particularly significant and is defined as the hedging point policy (HPP) in FPMS. Job shop problem is an NP-hard problem in terms of complexity (Garey, Tarjan, & Wilfong, 1988). Given that, the stochastic job shop problem is an NP-hard problem, as well, considering machine breakdown and variable processing speed.
In this study we try to evaluate the effect of individual factors to implementing the agility strategy in Isfahan municipality in the period of 1391-1392. Furthermore this study is considered as descriptive survey. The data gathering tool was a questionnaire consisted of 56 questions. To confirm the validity of questionnaire the teachers' academic advisors and some managers' opinions were used and SPSS software was used to measure the reliability of that; By using this software, Cornbrash's alpha equal to 0/974, respectively. This questionnaire was distributed between managers and employees upper than 13 grade of the municipality in a random way. The Statistical volume of the sample using Cochran formula and Morgan obtained 325. Research data using various statistical tests such as the Kolmogorov -Smirnoff, ranking Friedman, single-sample t and Pearson correlation were analyzed. Data analysis suggests that individual factors that include the level of professionalism of the staff, organizational commitment, and job motivation are effective to implementing the agility strategy.
Nowadays, the evaluation of the suppliers in order to improve the total performance of supply chain and increase the power of competitiveness, satisfaction and profitability of the company are considered important and significant issues at the organizations. The main objective of this research is to help oil and gas industry in order to evaluate and categorize the suppliers, using Fuzzy Inference System. The present research is empirical in terms of purpose and descriptive-survey in terms of data collection. Three outstanding managers of procurement department of the company under examination have been selected. With regard to the fact that, the number of identified Sub-indices to categorize the suppliers are too many in relevant literature, the Fuzzy Dematel method was used to determine the weight and importance of each of the Sub-indices suppliers. In the present paper, for evaluate and categorize the suppliers has been used from Fuzzy Inference System, with MATLAB Software.
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