When actors deem technological change undesirable, they may act symbolically by pretending to comply while avoiding real change. In our study of the introduction an algorithmic technology in a sales organization, we found that such symbolic conformity led unintendedly full implementation suggested To explain this surprising outcome, advance regime-of-knowing lens helps analyze deep challenges h...

The main purpose of this research is portfolio optimization in Tehran securities exchange using the black hole algorithm and the Gravitational Research algorithm. We also propose an algorithm named Hybrid Algorithm which combines the two algorithms above to cover the weaknesses of these two algorithms. Finally we compare the results with the Markowitz model and choose the optimal algorithm.<br ...

‎our contribution in this paper is to propose an iterative algorithm which does not require prior knowledge of operator norm and prove a strong convergence theorem for approximating a solution of split equality fixed point problem for quasi-nonexpansive mappings in a real hilbert space‎. ‎so many have used algorithms involving the operator norm for solving split equality fixed point problem‎, ‎...

with the rapid expansion of the information on the internet, recommender systems play an important role in terms of trade and research. recommender systems try to guess the user&apos;s way of thinking, using the in-formation of user&apos;s behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user&apos;s interest. ...

In today’s competitive world, the need to supply chain management (SCM) is more than ever. Since the purpose of logistic problems is minimizing the costs of organization to create favorable time and place for the products, SCM seek to create competitive advantage for their organizations and increase their productivity. This paper proposes a new multi-objective model for integrated forward / rev...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...