جستجوی مقالات مرتبط با کلیدواژه "gray wolf algorithm" در نشریات گروه "مدیریت"

Hospital waste collection is one of the most important issues in urban service management. In this research, a mathematical model is developed to partition demographic areas in the hospital services system. In this model, regarding the needs of some service providers, the hierarchical structure of the partitions is considered. For this purpose, in a unified decision-making process, populations are divided into main partitions, and then, each one is divided into a number of sub-partitions. The purpose of this type of segmentation is to provide an ordered structure to control the service flow from the operational level to managerial level. Since partitioning is an NP-hard problem, it is necessary to use meta-heuristic algorithms to solve numerical examples in the real world. Here, genetic and gray wolf algorithms have been developed to solve large-scale problems. Despite the high efficiency of both algorithms, the computational results showed that the gray wolf algorithm is more capable in solving large-scale problems. The results of this study can be used as a management tool in solving types of population-based partitioning problems, including the problems of health systems.

Transportation of pharmaceuticals as one of the most complex types of transportation has always been studied by researchers. This issue, which is a subset of a key issue called the transportation of hazardous substances, is one of the most integral and high-risk activities in the industrial activity cycle. Trying to find the optimal solution to this problem is one of the most useful topics in logistics. Accordingly, this study optimized the design of the drug logistics network. In this regard, the issue of vehicle routing (VRP) has been inspired. In this regard, the issue of vehicle routing (VRP) is inspired. To this end, first a conceptual model for this problem and a new mathematical model for routing drug transport vehicles with the role of path sensitivity and time window uncertainty are presented. In order to solve the problem, the Gray Wolf meta-heuristic algorithm has been used as a new and efficient algorithm. To evaluate the performance of the proposed algorithm, this algorithm is compared with the exact solution method and genetic algorithms and particle swarm and the results of the gray wolf algorithm show that this algorithm provides answers with the least possible error in a very short time.