Published on Mon Dec 19 2016

A modified Physarum-inspired model for the user equilibrium traffic assignment problem

Shuai Xu, Wen Jiang, Yehang Shou

The user equilibrium traffic assignment principle is very important in the solving of the traffic assignment problem. Mathematical programming models are designed to solve the user equilibrium problem in traditional algorithms. The Physarum model are notefficient in real traffic networks with two-way traffic characteristics.

0
0
0
Abstract

The user equilibrium traffic assignment principle is very important in the traffic assignment problem. Mathematical programming models are designed to solve the user equilibrium problem in traditional algorithms. Recently, the Physarum shows the ability to address the user equilibrium and system optimization traffic assignment problems. However, the Physarum model are not efficient in real traffic networks with two-way traffic characteristics and multiple origin-destination pairs. In this article, a modified Physarum-inspired model for the user equilibrium problem is proposed. By decomposing traffic flux based on origin nodes, the traffic flux from different origin-destination pairs can be distinguished in the proposed model. The Physarum can obtain the equilibrium traffic flux when no shorter path can be discovered between each origin-destination pair. Finally, numerical examples use the Sioux Falls network to demonstrate the rationality and convergence properties of the proposed model.

Mon Jun 09 2014
Artificial Intelligence
A bio-inspired algorithm for fuzzy user equilibrium problem by aid of Physarum Polycephalum
Physarum-type algorithm is developed to unify the Physarum network and the traffic network. The results demonstrate that our approach is competitive when compared with other existing algorithms.
0
0
0
Mon Oct 19 2020
Neural Networks
The Capacity Constraint Physarum Solver
Physarum polycephalum inspired algorithm (PPA) has attracted great attention. PPA could be used to solve system optimization or user equilibrium problems. Some problems require the flow flowing through links to follow capacity constraints. A novel framework is proposed to allow capacity constraints toward link flow in the PPA.
0
0
0
Fri Oct 04 2019
Machine Learning
Randomized Shortest Paths with Net Flows and Capacity Constraints
This work extends the randomized shortest paths (RSP) model by investigating the net flow RSP and adding capacity constraints on edge flows. The standard RSP is a model of movement, or spread, through a network interpolating between a random-walk and a shortest-path behavior.
0
0
0
Sat Apr 22 2017
Neural Networks
A hybrid primal heuristic for Robust Multiperiod Network Design
We investigate the Robust Multiperiod Network Design Problem. We propose a hybrid primal heuristic based on the combination of ant colony optimization and an exact large neighborhood search. We show that our heuristic can find solutions of extremely good quality with low optimality gap.
0
0
0
Wed Feb 24 2021
Artificial Intelligence
Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games
0
0
0
Wed Oct 07 2009
Artificial Intelligence
A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract)
Constrained Optimum Path (COP) problems appear in many real-life applications. Some of these problems have been considered and solved by specific techniques. In this paper, we introduce a novel local search modeling for some COPs by local search.
0
0
0