Omid Shafaghsorkh; Ashkan Ayough
Abstract
The purpose of this systematic review is to identify and categorize the application of soft operations research methods in healthcare settings. A systematic review was conducted to identify published papers on the application of soft operations research methods in the healthcare setting, using Google ...
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The purpose of this systematic review is to identify and categorize the application of soft operations research methods in healthcare settings. A systematic review was conducted to identify published papers on the application of soft operations research methods in the healthcare setting, using Google Scholar, Scopus, PubMed, Emerald, Elsevier, Web of Science, and ProQuest databases through December 2021. A total of 69 papers met our selection criteria for the systematic review. Soft operations research methods were used in a wide range of healthcare fields, including healthcare management, health informatics, e-health, and medical education, for identifying requirements, problem-solving, system design and implementation, process improvement, policymaking, knowledge management, and managing resilience, and marketing. This study contained restrictions on access to the full text of some articles and dissertations that had little impact on the study’s quality. The present study demonstrates the use of soft operations research methods in various areas of the healthcare system to better understand problematical situations. This paper can help to use soft operations research methods further in the healthcare problems, especially in the design and implementation of e-health and emerging new technology.
Ashkan Ayough
Abstract
Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature ...
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Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature of cost parameters. Considering the importance of coping with customer demand in different periods at different and variable rates, in this research, demand is considered fuzzy and the APP decisions modeled through a bi-objective LP model optimizing production and workforce level costs. The APP decisions are taken in two rounds, First The fuzzy model is transformed to a crisp goal programming counterpart and in the second round as the principal contribution of this paper, the APP decisions for rest of the horizon are updated based on actual demand occurred during starting periods. By generating several sample problems and using the Lingo, the validity of the proposed model is shown.