The Research about Simulated Annealing Ant Colony Algorithm in Emergency Logistics Path Optimization

2012 ◽  
Vol 482-484 ◽  
pp. 2470-2474 ◽  
Author(s):  
Li Yi Zhang ◽  
Teng Fei ◽  
Yun Shan Sun
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Economic Benefit ◽  
Ant Colony Algorithm ◽  
High Efficiency ◽  
Ant Colony ◽  
Path Optimization ◽  
Logistics Distribution ◽  
Emergency Logistics

Emergency logistics distribution, as an important role, is the key to the whole logistics. Emergency logistics is mainly reflected in emergency. For the disaster, economic benefit is not the first thing to be thought about. High efficiency is the key to emergency logistics. This article concentrates on path optimization of emergency logistics distribution. Propose emergency logistics distribution path optimization model which considers timeliness as the first goal. Utilize Simulated Annealing Ant Colony Algorithm to search for optimization. Based on simulation, Simulated Annealing Ant Colony Algorithm owns better timeliness to solve emergency logistics distribution.

The Research of Emergency Logistics Routing Optimization Based on Improved Ant Colony Optimization

2012 ◽  
Vol 482-484 ◽  
pp. 2519-2523
Author(s):  
Teng Fei ◽  
Li Yi Zhang ◽  
Yun Shan Sun ◽  
Hong Wei Ren
Keyword(s):  
Mathematical Model ◽  
Ant Colony Algorithm ◽  
Model Solution ◽  
Ant Colony ◽  
Traffic Situation ◽  
Logistics System ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Emergency Logistics ◽  
Improved Ant Colony Algorithm

Emergency logistics system contains information on material reserves, emergency command and emergency distribution. In this paper, the aspect of emergency distribution only is analyzed in microscopic, mathematical model of emergency logistics distribution has been established in considering the traffic situation and shortage degree. On the aspect of model solution, improved ant colony algorithm, which can enhance the selectivity of finding the best solution in emergency logistics distribution routing, is used in solving the model.

Application Research about the Chaos Ant Colony Algorithm in Emergency Logistics Distribution Routing Optimization

2011 ◽  
Vol 268-270 ◽  
pp. 1733-1738
Author(s):  
Teng Fei ◽  
Li Yi Zhang ◽  
Hong Wei Ren ◽  
Jin Zhang ◽  
Cui Wen Huang
Keyword(s):  
Quantitative Methods ◽  
Ant Colony Algorithm ◽  
Mathematic Model ◽  
Ant Colony ◽  
Experimental Simulation ◽  
Application Research ◽  
The Real ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Emergency Logistics

In this essay, the solution about emergency logistics distribution routing optimization has been analyzed by quantitative methods, and the mathematic model focusing on trying the best to shorten distribution time has been established, in which the actual situations of the pathways and the shortage of goods at each affected point have been considered in order to keep further close to the real circumstances where had suffered disaster. Using the Chaos Ant Colony Algorithm solves the mathematic model. The experimental simulation indicates that the arithmetic is feasible and effective to settle the problem about the optimization of emergency logistics distribution route.

Application of Emergency Logistics Distribution Routing Optimization Based on Improved Ant Colony Algorithm

2011 ◽  
Vol 268-270 ◽  
pp. 1726-1732 ◽  
Author(s):  
Li Yi Zhang ◽  
Teng Fei ◽  
Jin Zhang ◽  
Jie Li
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Delivery Time ◽  
Emergency Relief ◽  
Logistics Distribution ◽  
The Road ◽  
Routing Optimization ◽  
Emergency Logistics ◽  
Improved Ant Colony Algorithm

Emergency relief has characteristics of complexity, urgency, sustainability, technicality, and so on. In this paper a mathematical model to seek the shortest delivery time as the ultimate goal is established based on these characteristics, which is on the core of characteristics with the urgency and consider both the road conditions and on shortage of demand point of relief supplies. The problem of emergency logistics distribution routing optimization is solved by the improved ant colony algorithm—Fish-Swarm Ant Colony Optimization (FSACO), simulation results show that, compared with basic ant colony algorithm, Fish-Swarm Ant Colony Optimization can find the higher quality to solve the problem of emergency logistics distribution routing optimization.

scholarly journals The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Liyi Zhang ◽  
Ying Wang ◽  
Teng Fei ◽  
Hongwei Ren
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Ant Colony Algorithm ◽  
Optimization Problems ◽  
Ant Colony ◽  
Path Optimization ◽  
Low Carbon ◽  
Economic Activities ◽  
Logistics Industry ◽  
Routing Optimization

As the energy conservation and emission reduction and sustainable development have become the hot topics in the world, low carbon issues catch more and more attention. Logistics, which is one of the important economic activities, plays a crucial role in the low carbon development. Logistics leads to some significant issues about consuming energy and carbon emissions. Therefore, reducing energy consumption and carbon emissions has become the inevitable trend for logistics industry. Low carbon logistics is introduced in these situations. In this paper, from the microcosmic aspects, we will bring the low carbon idea in the path optimization issues and change the amount of carbon emissions into carbon emissions cost to establish the path optimization model based on the optimization objectives of the lowest cost of carbon emissions. According to different levels of air pollution, we will establish the double objectives path optimization model with the consideration of carbon emissions cost and economy cost. Use DNA-ant colony algorithm to optimize and simulate the model. The simulation indicates that DNA-ant colony algorithm could find a more reasonable solution for low carbon logistics path optimization problems.

Optimization of Spiral Drum Based on Improved Ant Colony Algorithm

2011 ◽  
Vol 403-408 ◽  
pp. 3022-3025
Author(s):  
Duan Yi Wang
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Economic Benefit ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Loading Capacity ◽  
Matlab Software ◽  
Working Principle ◽  
Working Performance ◽  
Improved Ant Colony Algorithm

Spiral drum as the work device of sheer, plays an important role for working performance and economic benefit .By analyzing the working principle of ant colony algorithm and its deficiencies; it proposed an improved ant colony algorithm to realize the optimization of spiral drum. In the paper, optimization model is established with coal-loading capacity as the objective function, and it make use of Matlab software to realize optimization of spiral drum.

Sign in / Sign up

Export Citation Format

Share Document