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Item type:Publication, A step-by-step hybrid approach based on multi-criteria decision-making methods and a bi-objective optimization model to project risk management(Regional Association for Security and crisis management, 2024-01-01)Project success and achieving project objectives and goals highly depend on effective and thorough risk management implementation. This study provides a comprehensive and practical methodology for project risk management. In this paper, firstly, the risks were collected by analyzing the historical documents and literature. Then, the collected risks were screened using brainstorming and categorized into five groups. Subsequently, a questionnaire was made and the identified risks were validated using the Fuzzy Delphi technique. Also, the relationships between risks were determined using the Interpretive Structural Modelling (ISM) method. Moreover, the weights of the criteria used to rank the risks were calculated through the Fuzzy Best-Worst Method. Subsequently, the major risks were determined using the fuzzy WASPAS method. Furthermore, a novel bi-objective mathematical programming model was developed and solved using the Augmented Epsilon-Constraint (AEC) method to choose the optimal risk response strategies for each critical risk. The results demonstrated that the proposed framework is effective in dealing with construction project risks. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A fuzzy bi-objective mathematical model for perishable medical goods supply chain network considering crisis situations: An empirical study(SAGE Publications Ltd, 2024-01-01)In case of crisis, the salvation of injuries depends on the timely provision of medical goods, relief supplies, and equipment. The aim of this study is to present a mathematical model for the supply chain network of perishable medical goods in crisis situation considering the uncertain environment. In this paper, a three-level supply chain including suppliers, intermediate warehouses, and final customers is developed for perishable medical items. The uncertainty of customer demand for service and the spent time in the intermediate warehouses are considered using the exponential distribution functions. Also, it is assumed that the life-cycle of perishable medical goods follow the Weibull distribution function. The model attempts to minimize the total costs of the supply chain and total presence time of perishable items in the whole chain. The LP-Metric method is employed for solving small-sized problems. Due to the NP-Hardness of the problem, the modified Multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II) are utilized as 2 well-known and efficient meta-heuristic algorithms for solving large-sized problems. The findings indicate that the meta-heuristic algorithms are efficient in achieving close to the optimal solution for large-size problems in a reasonable time. Also, the results demonstrate that NSGA-II outperforms MOPSO in terms of the high quality solution. Finally, the applicability of the model to real-world problems is demonstrated using a real case study. This paper can assist the planners and decision-makers of perishable drugs supply chain networks in crisis conditions with on-time supplying and distributing the required emergency items. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Performance Evaluation Optimization Model with a Hybrid Approach of NDEA-BSC and Stackelberg Game Theory in the Presence of Bad Data(Bucharest University of Economic Studies, 2023-01-01)The evaluation of organisational performance and internal power is of the most significance for any organisation. The purpose of this paper is to present a hybrid approach using Network Data Envelopment Analysis (NDEA), BSC, and Game Theory to evaluate the performance of decision-making units. To evaluate the efficiency of each decision-making unit, the relationship between different departments within an organisation is modeled based on the BSC indicators (growth and learning perspective, internal processes perspective, customer perspective, and financial perspective). Also, the influence of each of the BSC indicators on the efficiency of the decision-making units is examined using Game Theory and Stackelberg Theory. Moreover, the indicators related to each aspect of the BSC are expressed as input/output to determine performance. The proposed model has been implemented in 15 different cement factories based on the information obtained in 2021. The results reveal that the customer perspective has the greatest impact on the performance of the entire organisation and plays a crucial leading role in the organisation. Among the followers, the perspective of internal processes that is influenced by the leader strategy (customer perspective) is ranked first, and the perspectives of growth, learning, and finance are ranked second, third, and fourth, respectively. This research facilitates managerial decision-making for the optimal allocation of resources to increase the performance and profitability of the organisation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Hybrid Metaheuristic Approach for Solving a Bi-Objective Capacitated Electric Vehicle Routing Problem with Time Windows and Partial Recharging(Emerald Publishing, 2023-10-10)The vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development. Design/methodology/approach: In this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS). Findings: The results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis. Originality/value: In this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.