Time dependent vehicle routing problem with a multi ant colony system

2008 ◽  
Vol 185 (3) ◽  
pp. 1174-1191 ◽  
Author(s):  
Alberto V. Donati ◽  
Roberto Montemanni ◽  
Norman Casagrande ◽  
Andrea E. Rizzoli ◽  
Luca M. Gambardella
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Time Dependent ◽  
Ant Colony System ◽  
Routing Problem

The Application of a Improved Hybrid Ant Colony Algorithm in Vehicle Routing Optimization Problem

2014 ◽  
Vol 556-562 ◽  
pp. 4693-4696
Author(s):  
Yue Li Li ◽  
Ai Hua Ren
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Ant Colony System ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
Constrained Vehicle Routing ◽  
Capacity Constrained

With the development of the market economy, the logistics industry has been developed rapidly.It is easy to understand that good vehicle travel path planning has very important significance in the logistics company,especially in the general production enterprises. This paper mainly studies the microcosmic traffic system in the type of vehicle routing problems: capacity-constrained vehicle routing problem. We demonstrate the use of Ant Colony System (ACS) to solve the capacitated vehicle routing problem, treated as nodes in a spatial network. For the networks where the nodes are concentrated, the use of hybrid heuristic optimization can greatly improve the efficiency of the solution. The algorithm produces high-quality solutions for the capacity-constrained vehicle routing problem.

A Hybrid Algorithm for the Multi-Objective Time Dependent Vehicle Routing Problem

2014 ◽  
Vol 505-506 ◽  
pp. 1071-1075
Author(s):  
Yi Sun ◽  
Yue Chen ◽  
Chang Chun Pan ◽  
Gen Ke Yang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Algorithm ◽  
Time Windows ◽  
Time Dependent ◽  
Ant Colony System ◽  
Optimal Solutions ◽  
Test Results ◽  
Routing Problem ◽  
Traffic Conditions

This paper presents a real road network case based on the time dependent vehicle routing problem with time windows (TDVRPTW), which involves optimally routing a fleet of vehicles with fixed capacity when traffic conditions are time dependent and services at customers are only available in their own time tables. A hybrid algorithm based on the Genetic Algorithm (GA) and the Multi Ant Colony System (MACS) is introduced in order to find optimal solutions that minimize two hierarchical objectives: the number of tours and the total travel cost. The test results show that the integrated algorithm outperforms both of its traditional ones in terms of the convergence speed towards optimal solutions.

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