Knowledge Extraction
Manya Sadat Hashemian; Javad Rezaian; Amir Gholam Abri
Abstract
The aim of the current research was to provide an intelligent model of the green supply chain of pharmaceutical products with the overlap of common customers. This research applies simulation to the proposed model of a pharmaceutical supply chain with smart and green conditions. The society under investigation ...
Read More
The aim of the current research was to provide an intelligent model of the green supply chain of pharmaceutical products with the overlap of common customers. This research applies simulation to the proposed model of a pharmaceutical supply chain with smart and green conditions. The society under investigation is the environment of pharmaceutical companies, with its specific assumptions and goals. This model is simulated in the GMAS software environment. The problem was examined from two perspectives: simultaneous production (coordination of drugs) and cooperative planning (coordination of suppliers). Additionally, in order to address the issue of vehicle routing under real conditions of limited capacity for delivery vehicles, the expiration date of the drug and time windows in orders were taken into consideration. The objective was to allocate orders to vehicles in a way that minimizes the total delivery time and reduces the amount of carbon dioxide produced. Based on the obtained results, this multi-objective model aims to improve the performance of the pharmaceutical distribution network by addressing three main complexities: economic, environmental, and social. This approach provides a comprehensive and balanced solution for designing the drug distribution network. Its goal is to preserve the environment, improve social conditions, and maximize economic profit.
Data mining
Seyed Rohollah Abbasi; Abdul Khalegh Gholami Chenaristan Alia; Foad Makvandi
Abstract
This study aimed to design a data-driven decision-making model for managers in the direction of empowering human resources in the police headquarter of Kohgiluyeh and Boyer-Ahmad province. Increasing amount of information and rapid changes in the environment and the need to create continuous communication ...
Read More
This study aimed to design a data-driven decision-making model for managers in the direction of empowering human resources in the police headquarter of Kohgiluyeh and Boyer-Ahmad province. Increasing amount of information and rapid changes in the environment and the need to create continuous communication with the complex and dynamic environment requires management, acquisition and distribution of knowledge as well as, proper organizing and analysis of information. The present research uses a qualitative approach. The statistical population included experts in the police force, 19 people were selected through purposive sampling and interviewed. The identified indicators of the data-driven decision-making model of managers in empowering employees were extracted in the form of 3 main categories, 17 sub-categories, and 69 concepts. The identified model was also tested based on the AdaBoost regression algorithm in Rapidminer software which led to development of the intelligence of the managers' decision-making model compared to the traditional model. The findings showed structural factors (including strategic orientations, organizational structure dynamics, performance management system, training and improvement, knowledge management system, job design system, and information technology system) behavioral factors (including management orientations, leadership style, development of psychological characteristics of employees), development of decision-making skills and competences of employees, human relations system, job attitudes, and organizational culture) and environmental factors (including legal factors, political factors, and economic factors). Based on the proposed model, the accuracy of data-driven decision-making of managers was tested and the results indicated the significance of intelligence and information in the organization.