bee algorithm

Selecting suitable suppliers and assigning orders to them, is one of the most important strategic supply chain management activities. In this research, a mathematical model for choosing the supplier in the supply chain in the framework of the operational research methods in dairy production units in the city of maku was proposed. The model was designed as Linear programming with assumptions such as supplying a variety of milk products with the same requirements, such as quality, timely delivery, obligations and envirmental require mental for all suppliers. This model includes parameters such as milk purchase cost, transportation cost, milk purchase, milk suppliers, production capacity, and minimum required milk. The objectives of this research include minimizing the cost of supplying milk, supplying the minimum required milk and selecting suitable suppliers of milk. the research method, mathematical descriptive, is applied in terms of purpose, Information gathering tools, such as documentation tools, interviews with experts and production managers were used in relation to production, to determine the sample size were selected by cluster sampling method and random sampling method. Due to complexity of the problem solving, the meta-heuristic bee algorithm approach using MATLAB software was solved. The results obtained from the findings showed that with the bee algorithm, the suitable supplier of milk was selected in the supply chain, so that the cost of milk supply minimized and the minimum material required was estimated by the suppliers. It is Conclude that the suggested bee algorithm is an acceptable performance in a suitable time period.

The purpose of this study is to investigate the application of Meta Heuristic Algorithms in Financial field. The studied algorithms in this study include ant colony algorithm, firefly algorithm, bee algorithm, harmony search, biogeography algorithm. while examining each of these algorithms in brief, internal and external studies are performed and their applications in the financial field are discussed. The results show that further research and ultimately the use of these algorithms in predicting financial and capital market issues can help to increase the performance of accounting and auditing operations to a researchable extent. Increasing research and providing operational backgrounds in recent years also reflect the interest of researchers and research organizations in developing these new approaches, especially in the field of software development.