scholarly journals A New Mathematical Method for Solving Cuttings Transport Problem of Horizontal Wells: Ant Colony Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Liu Yongwang ◽  
Liu Yu-ming ◽  
Qiu Heng-bin ◽  
Bai Yan-feng
Keyword(s):  
Objective Function ◽  
Nonlinear Equations ◽  
Ant Colony Algorithm ◽  
Transport Model ◽  
Horizontal Wells ◽  
Ant Colony ◽  
Transport Problem ◽  
Optimization Process ◽  
Cuttings Transport ◽  
Highly Nonlinear

Cuttings transport problem has long been recognized as one of the key difficulties in drilling horizontal wells, and the models in cuttings transport research are usually formulated with highly nonlinear equations set. When using Newton methods to solve real engineering problems with nonlinear equations set, the problems of result dependence on initial values, Jacobian matrix singularity, and variable outflow of its definition domain in iterations are three of the often-encountered difficulties. In this paper, the ant colony algorithm is applied to solve the two-layer cuttings transport model with highly nonlinear equations set. The solution-searching process of solving nonlinear equations set is transformed into an optimization process of searching the minimum value of an objective function by applying ant colony algorithm. Analyzing the results of the example, it can be concluded that ant colony algorithm can be used to solve the highly nonlinear cuttings transport model with good solution accuracy; transforming the solution-searching process of solving nonlinear equations set into an optimization process of searching the minimum value of the objective function is necessary; the real engineering problem should be simplified as much as possible to decrease the number of unknown variables and facilitate the use of ant colony algorithm.

The Multi-Site Joint Operation Method Based on Discharge Gate Ant Colony Algorithm

2014 ◽  
Vol 721 ◽  
pp. 539-542
Author(s):  
Cong Cong Liu ◽  
Yi Cai He ◽  
Chang Peng An
Keyword(s):  
Objective Function ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Operating Costs ◽  
Joint Operation ◽  
Function Model ◽  
Target Weight ◽  
Actual Operation ◽  
The Right ◽  
Improved Ant Colony Algorithm

From the actual operation of the lock, respectively, with the objections to maximize utilization of the average chamber area and minimize average opening time and the product of the weight of the ship and minimize lock operating costs, it can make the use of AHP calculate the right target weight, so as to establish a multi-objective function model. Based on the constraints of each objection, it can be used improved ant colony algorithm for multi-site on the same river ship Joint operation, using MATLAB software for solving scheduling simulation, the results shows that the utilization and lock navigable levels have significantly improved . It proved this method can be used to optimize multi-site joint scheduling.

Dual Objective Multidimensional Parameter Optimization of Cam Curve Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 1037 ◽  
pp. 357-362
Author(s):  
Zhen Jun He ◽  
Peng Xu ◽  
Jiang Xiao Liao
Keyword(s):  
Objective Function ◽  
Ant Colony Algorithm ◽  
Weight Coefficient ◽  
Ant Colony ◽  
Multidimensional Space ◽  
Profile Curve ◽  
Multi Objective ◽  
Cam Mechanism ◽  
Variable Weight ◽  
Improved Ant Colony Algorithm

By applying improved ant colony algorithm, this paper analyzed multi-objective design problem in optimal design of cam mechanism profile curve, which were then transformed into TSP problem, that is, multi-objective function minimization problem into TSP shortest path searching problem. For the multiple complex variables and target weight parameters in design, a concept of multidimensional space node in ant colony optimization path was proposed, converting multi-objective function with weight coefficient into a multidimensional space nodes (city).At the same time, improved ant colony algorithm, combined with genetic algorithm, was used to avoid optimization calculation falling into a locally optimal solution. Exemplified by dual objective function in cam mechanism profile curve design, this paper solved optimal value problem of dual objective optimization design involving the biggest fullness coefficient and minimum abrasion quantity of variable weight coefficient under the three-dimensional parameters n, m and w.

An Improved Quantum Ant Colony Algorithm of Solving Nonlinear Equation Groups

2014 ◽  
Vol 1049-1050 ◽  
pp. 1363-1366 ◽  
Author(s):  
Yue Hua Xia ◽  
Yue Guang Li
Keyword(s):  
Nonlinear Equation ◽  
Nonlinear Equations ◽  
Ant Colony Algorithm ◽  
Global Search ◽  
Ant Colony ◽  
Experimental Result ◽  
The Core ◽  
Quantum Rotation Gate

In this paper, according to the characteristics of nonlinear equations. A new algorithm, Quantum Ant Colony Algorithm (QACA) is proposed. The core is that Q-bit and quantum rotation gate adopted in QEA are introduced into ACS to represent and update the pheromone respectively, so it has better diversity and global search capacity. The experimental result demonstrates that QACA can get better solutions to nonlinear equations.

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.

Hybrid Behavior Ant Colony Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 4496-4499 ◽  
Author(s):  
Xian Min Wei
Keyword(s):  
Convergence Rate ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Optimization Process ◽  
Algorithm Optimization ◽  
Ant Behavior

In basic ant colony algorithm optimization process, for the ant colony algorithm in speeding up the convergence rate and avoiding stagnation, ant colony algorithm based on hybrid behavior is studied in this paper. By the ant behavior definition and implementation of the algorithm, the instance confirms that the ant colony algorithm based on hybrid behavior has a more stable solving performance than the basic ant colony algorithm.

scholarly journals Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune–Ant Colony Algorithm

2020 ◽  
Vol 17 (16) ◽  
pp. 5831 ◽  
Author(s):  
Ziyuan Liu ◽  
Zhi Li ◽  
Weiming Chen ◽  
Yunpu Zhao ◽  
Hanxun Yue ◽  
...  
Keyword(s):  
Public Health ◽  
Ant Colony Algorithm ◽  
Transport Model ◽  
Medical Waste ◽  
Immune Algorithm ◽  
Ant Colony ◽  
Transportation Demand ◽  
Temporary Storage ◽  
Assessment Guidelines ◽  
Health Event

In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony–tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China—considered the first city to suffer from COVID-19—was chosen as an example of verification; the two-level model and the immune algorithm–ant colony optimization–tabu search (IA–ACO–TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.

Path Planning and Replanning for Intelligent Robot Based on Improved Ant Colony Algorithm

2013 ◽  
Vol 390 ◽  
pp. 495-499 ◽  
Author(s):  
Bi Wei Tang ◽  
Zhan Xia Zhu ◽  
Qun Fang ◽  
Wei Hua Ma
Keyword(s):  
Path Planning ◽  
Objective Function ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Local Optimum ◽  
Intelligent Robot ◽  
Intelligent Robots ◽  
Simulation Results ◽  
Improved Ant Colony Algorithm ◽  
Self Adaptive

The effectiveness of path planning and path replanning for intelligent robot using improved ant colony algorithm is explored in this paper. For the purpose of avoiding falling into local optimum and preventing iterative stagnant, this paper describes a new algorithm named stochastic self-adaptive ant colony algorithm to improve the basic ant colony algorithm. Based on the improved ant colony algorithm, the approaches of path planning and path replanning are presented in this paper. Aiming at improving the speed of the algorithm and simplifying the objective function of traditional path planning, this paper presents a principle of eliminating the path nodes .Finally, some constrast emulators are designed.The simulation results proves that the improved ant colony algorithm has strong adaptability in intelligent robots path path planning and replanning.

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