firefly algorithm

Today, natural disaster is threatening the lives of people and their assets and properties.Relief supply chain is the most agile and dynamic supply chain. Indeed, the pivotal role of relief supply chainhas been identified in responding to crises and reducing the burden on humans. In this regard, the goal of allocatingand locating issues is to allow each injured person to receive the services and goods from the distributioncenters according to demand, and suppliers will also provide goods and services for the distribution centers. Thepresent study tried to provide a mathematical model for the problem of allocating earthquake victims to existingand potential hospitals using ultra-innovative algorithms. For this purpose, first, the design of its mathematicalmodel and its innovation aimed at minimizing the costs of establishing potential hospitals, sending injured peopleand sending services and goods from suppliers to hospitals. Then, the validation and accuracy of the mathematicalmodel were evaluated using Gamz software. In the next step, acceptable results were obtained with codingin MATLAB, using fire suppression algorithms and optimizing particle swarm. After the efficiency was established,the problem test was used for the data in order to compare the algorithms. Finally, it was identified thatthe particle swarm optimization algorithm was superior to the firewall algorithm in both runtime and cost values.

Nowadays the growth in the use of social networks among different classes of world community is increasingly undeniable. Social networks database include Rich and valuable resources whose release and analysis with the purpose of marketing, publicity, National Security, Health and etc. can benefit researchers of public and private institutions. But respect the privacy of the entities whose information is available to data miner analysis is essential as a legal protocol. In this Paper, through qualitative methodology Meta synthesis, all related dimensions, indicators and codes were identified and then the importance and priority of each of the factors was determined. Subsequently, the improved model of anonymity was presented by an optimizing firefly algorithm and fuzzy clustering. The result of simulation and assessment of the proposed model on the data of four social networks such as Facebook, YouTube, Twitter and Google+ depicts that privacy preserving of data with the lowest distortion ratio and the more usefulness of data.

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.