Improved ant colony genetic optimization algorithm and its application

Liu, Chuanling

doi:10.3724/sp.j.1087.2013.03111

Cited by 3 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Be that as it may, multi-jump steering acquaints noteworthy overhead relating with topology the executives and MAC. All things considered, detailing vitality rationing types of correspondence and calculation are basic particularly in a multi jump condition [34].…”

Section: Energy Preservationmentioning

confidence: 99%

Energy efficiency enhancement in wireless sensor network: ant colony optimization

Kumar,

Jebarani

2023

IJEECS

View full text Add to dashboard Cite

<p><span>Wireless sensor networks (WSNs) have received significant scholarly attentionwithin the scientific community lately. The use of small and energy efficient devices with restricted computing capabilities has gained traction in various fields of application, including environmental monitoring, target tracing, and medical health observation. Node localization is a fundamental system parameter in numerous applications. Categorizing hybrid solutions as either range-based or range-free poses a challenge in general. In this article, we aim to simplify the classification process by examining range-based and range-free schemes. There are two distinct classifications of schemes, namely fully schemes and hybrid schemes. Furthermore, we conduct a comparative analysis of the predominant energy efficiency measures in WSN networks and deliberate on prospective avenues for research in WSNs deploying ant colony algorithm.</span></p>

show abstract

Section: Energy Preservationmentioning

confidence: 99%

Energy efficiency enhancement in wireless sensor network: ant colony optimization

Kumar,

Jebarani

2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…(7) Judging the termination conditions. If the condition is not satisfied, go to step (8). If satisfied, output the optimal route and the intelligent vehicle advances according to the route through the assistance of RFID.…”

Section: Steps Of Evolutionary Ant Colony Algorithmmentioning

confidence: 99%

“…The environment mapI is as shown in Figure 12. The start point is S, and the destination point is G. We make the comparison with four algorithms: the evolutionary ant colony algorithm (EAC), the ant colony genetic algorithm (AC-GA) in [8], the improved ant colony algorithm (SA-AC) in [10], and the evolutionary genetic algorithm (EGA). There are two algorithms (EAC and EGA) based on experiential knowledge.…”

Section: Simulationmentioning

confidence: 99%

“…Although this method can solve the robot path planning problem, it is more complex and difficult. In order to improve execution speed and search efficiency, Liu [8] proposed an improved algorithm based on ant colony algorithm and genetic algorithm. Liu and Cheng [9] presented vision detection colony algorithm with elitist strategy to improve the efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Routing Optimization of Intelligent Vehicle in Automated Warehouse

Zhou

Dong

Xia

et al. 2014

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

Routing optimization is a key technology in the intelligent warehouse logistics. In order to get an optimal route for warehouse intelligent vehicle, routing optimization in complex global dynamic environment is studied. A new evolutionary ant colony algorithm based on RFID and knowledge-refinement is proposed. The new algorithm gets environmental information timely through the RFID technology and updates the environment map at the same time. It adopts elite ant kept, fallback, and pheromones limitation adjustment strategy. The current optimal route in population space is optimized based on experiential knowledge. The experimental results show that the new algorithm has higher convergence speed and can jump out the U-type or V-type obstacle traps easily. It can also find the global optimal route or approximate optimal one with higher probability in the complex dynamic environment. The new algorithm is proved feasible and effective by simulation results.

show abstract

Calibration of a simplified thermodynamic model for VVER-1200-based nuclear power plants using evolutionary algorithms

Amir

Khan

2022

2022 25th International Conference on Computer and Information Technology (ICCIT)

View full text Add to dashboard Cite

Improved ant colony genetic optimization algorithm and its application

Cited by 3 publications

References 0 publications

Energy efficiency enhancement in wireless sensor network: ant colony optimization

Energy efficiency enhancement in wireless sensor network: ant colony optimization

Routing Optimization of Intelligent Vehicle in Automated Warehouse

Calibration of a simplified thermodynamic model for VVER-1200-based nuclear power plants using evolutionary algorithms

Contact Info

Product

Resources

About