An improved ant colony optimisation and its application on multicast routing problem

2011 ◽  
Vol 5 (1) ◽  
pp. 18 ◽  
Author(s):  
Zhang Yi ◽  
Liu Yan chun
Keyword(s):  
Multicast Routing ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Routing Problem

Ant Colony Optimisation Model for Vehicle Routing Problem With Simultaneous Pickup and Delivery

2016 ◽  
Author(s):  
Robin Scanlon ◽  
Qing Wang ◽  
Jie Wang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Complex Problem ◽  
Ant Colony ◽  
Benchmark Problems ◽  
Pickup And Delivery ◽  
Ant Colony Optimisation ◽  
Routing Problem ◽  
Route Length ◽  
Simultaneous Pickup And Delivery

Reverse logistics is an area that has come under increased scrutiny in recent years as legislators and companies try to increase the amount of goods that businesses reuse and recycle. The vehicle routing problem with simultaneous pickup and delivery arises when firms want to reduce handling costs by dealing with deliveries and returns in one operation. This is a complex problem for planners who aim to minimise the vehicle route length as the vehicle load rises and falls during a tour of facilities. This paper investigates the use of Ant Colony Optimisation to find solutions to this problem. An algorithm combining elements of three different studies is proposed. The algorithm finds results within 0.2% of the best known results and performs well for half of the benchmark problems, but needs further work to reach the same level on the other half. It is found that the proposed changes can have up to a 3.1% improvement in results when compared to previous methods run on this algorithm.

A tree-growth based ant colony algorithm for QoS multicast routing problem

2011 ◽  
Vol 38 (9) ◽  
pp. 11787-11795 ◽  
Author(s):  
Hua Wang ◽  
Hong Xu ◽  
Shanwen Yi ◽  
Zhao Shi
Keyword(s):  
Tree Growth ◽  
Ant Colony Algorithm ◽  
Multicast Routing ◽  
Ant Colony ◽  
Routing Problem

scholarly journals Electric Vehicle Fleet Management Using Ant Colony Optimisation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-16
Author(s):  
Javier Biera Muriel ◽  
Abbas Fotouhi
Keyword(s):  
Limited Range ◽  
Ant Colony ◽  
Fleet Management ◽  
Ant Colony Optimisation ◽  
Routing Problem ◽  
Charging Time ◽  
Battery Degradation ◽  
Optimum Solution ◽  
Advanced Version

This research is focused on implementation of the ant colony optimisation (ACO) technique to solve an advanced version of the vehicle routing problem (VRP), called the fleet management system (FMS). An optimum solution of VRP can bring benefits for the fleet operators as well as contributing to the environment. Nowadays, particular considerations and modifications are needed to be applied in the existing FMS algorithms in response to the rapid growth of electric vehicles (EVs). For example, current FMS algorithms do not consider the limited range of EVs, their charging time or battery degradation. In this study, a new ACO-based FMS algorithm is developed for a fleet of EVs. A simulation platform is built in order to evaluate performance of the proposed FMS algorithm under different simulation case-studies. The simulation results are validated against a well-established method in the literature called nearest-neighbour technique. In each case-study, the overall mileage of the fleet is considered as an index to measure the performance of the FMS algorithm.

scholarly journals Application of Modified Ant Colony Optimization (MACO) for Multicast Routing Problem

2016 ◽  
Vol 8 (4) ◽  
pp. 43-48 ◽  
Author(s):  
Sudip Kumar Sahana ◽  
◽  
Mohammad AL-Fayoumi ◽  
Prabhat Kumar Mahanti
Keyword(s):  
Ant Colony Optimization ◽  
Multicast Routing ◽  
Ant Colony ◽  
Routing Problem

Improved ant colony optimisation for the dynamic multi-depot vehicle routing problem

2013 ◽  
Vol 16 (2) ◽  
pp. 144-157 ◽  
Author(s):  
Bin Yu ◽  
Ning Ma ◽  
Wanjun Cai ◽  
Ting Li ◽  
Xiaoting Yuan ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Routing Problem
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