Research on Parallel Scheduling of Maximize the Number of Task Processing under Time Constraints- an Example to De-Icing Operation

2011 ◽  
Vol 148-149 ◽  
pp. 1101-1106
Author(s):  
Bing Li ◽  
Xin Yue Fu ◽  
Dan Su ◽  
Gui Song Jiang
Keyword(s):  
Mathematical Model ◽  
Practical Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Time Constraints ◽  
Parallel Scheduling ◽  
Task Processing ◽  
The Mathematical Model ◽  
Full Consideration

Under the context of airplane deicing, this paper aims to do a research on the unrelated parallel scheduling of service resources with flexible time window. To deal with more tasks, minimizing delay time is chosen to be the objective of the mathematical model and a modified ant colony algorithm is given. With full consideration of the practical problem and constraints, update policy of pheromone and settings of heuristic factors are suggested. The feasibility and rationality are proved by a simulation example. The modified ant colony algorithm outperforms FIFO method and could be well applied in the unrelated parallel scheduling issues with flexible time window.

Study on the Path Optimized Method Based on an Improved Clustering Ant Colony Algorithm for CNC Laser Drilling

2014 ◽  
Vol 556-562 ◽  
pp. 4439-4442 ◽  
Author(s):  
En Te Guo ◽  
Ting Wu ◽  
Li Bing Zhang ◽  
Feng Li Huang
Keyword(s):  
Mathematical Model ◽  
Ant Colony Algorithm ◽  
Laser Drilling ◽  
Ant Colony ◽  
Path Optimization ◽  
Experimental Result ◽  
Machining Efficiency ◽  
Clustering Approach ◽  
The Mathematical Model ◽  
Improved Ant Colony Algorithm

In order to improve the machining efficiency of the CNC laser drilling, this paper presents the path optimized method based on an improved ant colony algorithm of the k-means clustering approach. The mathematical model of the path optimization is constructed, and the path optimized method based on the improved clustering ant colony algorithm is designed and actualized. The optimized path method for CNC laser drilling based on the improved clustering ant colony algorithm is tested, and the simulative and experimental result have shown that the proposed method is better performance, and the machining efficiency is greatly improved.

Optimization of Logistics Distribution Route Based on the Save Mileage Method and the Ant Colony Algorithm

2013 ◽  
Vol 448-453 ◽  
pp. 3683-3687 ◽  
Author(s):  
Qing Fan ◽  
Xing Xin Nie ◽  
Ke Yu ◽  
Xi Lin Zuo
Keyword(s):  
Mathematical Model ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Practical Application ◽  
Distribution Problem ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Single Vehicle ◽  
The Mathematical Model

This paper established the mathematical model of Logistics distribution routing problem,and departed the multiple vehicle routing problem into a single vehicle distribution problem with the save mileage method ,then the ant colony algorithm were used to optimize the single vehicle distribution problem. Finally through a case shows that the model for the practical application of logistics distribution has certain reference significance.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

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.

scholarly journals Contactless Distribution Path Optimization Based on Improved Ant Colony Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Feng Wu
Keyword(s):  
Customer Service ◽  
User Satisfaction ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Cost Model ◽  
Ant Colony ◽  
Path Optimization ◽  
Traffic Information ◽  
Research Areas ◽  
Improved Ant Colony Algorithm

In the context of the normalization of the epidemic, contactless delivery is becoming one of the most concerned research areas. In the severe epidemic environment, due to the frequent encounter of bayonet temperature measurement, road closure, and other factors, the real-time change frequency of each traffic information is high. In order to improve the efficiency of contactless distribution and enhance user satisfaction, this paper proposes a contactless distribution path optimization algorithm based on improved ant colony algorithm. First of all, the possible traffic factors in the epidemic environment were analyzed, and the cost of each link in the distribution process was modeled. Then, the customer satisfaction is analyzed according to the customer service time window and transformed into a cost model. Finally, the total delivery cost and user satisfaction cost were taken as the optimization objectives, and a new pheromone updating method was adopted and the traditional ant colony algorithm was improved. In the experiment, the effectiveness of the proposed model and algorithm is verified through the simulation optimization and comparative analysis of an example.

scholarly journals Clustering Control of Multi-Objective Problems with Application to E-commerce

2018 ◽  
Vol 1 (1) ◽  
pp. 41
Author(s):  
Liang Chen ◽  
Xingwei Wang ◽  
Jinwen Shi
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Distribution Area ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Multi Objective ◽  
The Cost ◽  
Vehicle Capacity ◽  
Cost Of Transportation

In the existing logistics distribution methods, the demand of customers is not considered. The goal of these methods is to maximize the vehicle capacity, which leads to the total distance of vehicles to be too long, the need for large numbers of vehicles and high transportation costs. To address these problems, a method of multi-objective clustering of logistics distribution route based on hybrid ant colony algorithm is proposed in this paper. Before choosing the distribution route, the customers are assigned to the unknown types according to a lot of customers attributes so as to reduce the scale of the solution. The discrete point location model is applied to logistics distribution area to reduce the cost of transportation. A mathematical model of multi-objective logistics distribution routing problem is built with consideration of constraints of the capacity, transportation distance, and time window, and a hybrid ant colony algorithm is used to solve the problem. Experimental results show that, the optimized route is more desirable, which can save the cost of transportation, reduce the time loss in the process of circulation, and effectively improve the quality of logistics distribution service.

Research on Optimization Model of Vehicle Routing for Emergent Relief Supplies of Multi-Reserves

2010 ◽  
Vol 171-172 ◽  
pp. 205-210
Author(s):  
Tong Zhao ◽  
Hou Ming Fan ◽  
Gui Lin Wang
Keyword(s):  
Mathematical Model ◽  
Natural Disasters ◽  
Vehicle Routing ◽  
Optimization Model ◽  
Ant Colony Algorithm ◽  
Well Being ◽  
The World ◽  
High Level ◽  
The Mathematical Model ◽  
Improved Ant Colony Algorithm

In the world today, science and technology in natural disasters forecasting is changing with each passing day and is built up to a rather high level. But local, territorial, even just national or worldwide scope natural disasters have also posed a grave menace to human well-being and development. Therefore, researching on optimizing problem of vehicle routing for emergent relief supplies of multi-reserves, it is vital significant to quickly send relief supplies to the sufferers after sudden natural disasters. Then, we draw out the mathematical model and solve the problem reasonably based on the improved ant colony algorithm, at last, we obtain the satisfy results through an empirical exemple.

scholarly journals Distribution of Combat Capabilities on Objectives by Using a Transport Problem

2017 ◽  
Vol 23 (1) ◽  
pp. 15-20
Author(s):  
Alexandru Baboș ◽  
Alina-Mihaela Baboș
Keyword(s):  
Mathematical Model ◽  
Transportation Problem ◽  
Practical Problem ◽  
Transport Problem ◽  
Resources Allocation ◽  
Real Problem ◽  
Optimal Plan ◽  
Military Action ◽  
The Real ◽  
The Mathematical Model

Abstract The transport problem finds its application in situations where the upper echelons must draw up an optimal plan of resources allocation for combat capabilities on objectives. In order to achieve more reliable results for the real problem, the data needed to formulate the mathematical model are extracted from an order of operations. This paper presents the optimization of military action, showing how to solve a practical problem using the transportation problem.

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