title: A bio-inspired method for the constrained shortest path problem.
abstract: The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method.
authors: School of Computer and Information Science, Southwest University, Chongqing 400715, China.
authors: Hongping
authors: H
authors: Wang
authors: School of Computer and Information Science, Southwest University, Chongqing 400715, China.
authors: Xi
authors: X
authors: Lu
authors: School of Computer and Information Science, Southwest University, Chongqing 400715, China.
authors: Xiaoge
authors: 0000-0001-6831-3175
authors: X
authors: Zhang
authors: School of Computer and Information Science, Southwest University, Chongqing 400715, China.
authors: Qing
authors: Q
authors: Wang
authors: School of Computer and Information Science, Southwest University, Chongqing 400715, China ; School of Engineering, Vanderbilt University, Nashiville, TN 37235, USA.
authors: Yong
authors: 0000-0002-5481-5673
authors: Y
authors: Deng
mesh_terms: D000465:Algorithms; D016571:Neural Networks, Computer