Meta-heuristic bus transportation algorithm

Abstract

Over recent decades, several experience-based mathematical models have been proposed. In addition to collective intelligence, in recent years some efforts have been made to apply human experience-based intelligence to open up a new world of possibilities to design new meta-heuristic algorithms for solving NP problems. In these algorithms instead of only relying on collective intelligence, each individual tries to search for optimal solution based on her or his own experience and others. In this paper, we use a social behavior of humans in transportations to reach their destination and we took experience-based human behavior and smartness of humans as an inspiration to propose our meta-heuristic algorithm and we name it bus transportation algorithm. As a simple example, we restrict our paper to solve a well-known problem integer programming which is known as an NP-Complete problem. Compared to other algorithms, the results in these papers show that our algorithm outperforms PSO (particle swarm optimization), GA (genetic algorithm) and SA (simulated annealing) in terms of efficiency and convergence.