Investigating the dimensions of globalization and its impact on poverty in Iran: An improved bat algorithm approach

Abstract

Collective intelligence is one of the most powerful optimization techniques based on group behaviors of organisms. Bat algorithm (BA) is an algorithm inspired by the collective action of bats in the wild, presented in 2010 by Yang. Researchers have made several efforts to improve these algorithms. This article investigates the effect of globalization on Iran's poverty by enhancing the performance of BA. As an inescapable reality, globalization has various political, social, and economic dimensions, each with different effects on poverty. In this article, to improve the algorithm's performance, the speed and motion relationships of bats were modified such that to adapt the movement of bats as optimization solutions toward the target. The mutation operator is also used to check all points of the search space to get rid of the optimal local optimization. The study period is the years 1995 to 2017. The results showed that globalization affects Iran's poverty in various dimensions, and the performance of the improved bat collective intelligence algorithm (ISABA) for modeling is better than that of the bat algorithms (BAs). • This article provides a suitable method for researchers to study poverty. • Improved BAs can help researchers solve complex problems. • The results obtained by the collective intelligence algorithms in this paper help researchers in the field of poverty to compare the results of their research with it.

Keywords

• Globalization
• Poverty
• Improved bat algorithm
• Optimization