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1
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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2
DACS3:Embedding Individual Ant Behavior in Ant Colony System
Published 2008“…Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). …”
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3
Formulation of metaheuristic algorithms based on artificial bee colony for engineering problems
Published 2024“…The Artificial Bee Colony (ABC) algorithm is a powerful metaheuristic optimization technique inspired by the honeybee foraging behaviour. …”
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4
DACS3: Embedding Malaysian Individual Ant Behavior in Ant Colony System
Published 2009“…Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). …”
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Citation Index Journal -
5
Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).
Published 2007“…Ants are a fascinating creature that demonstrates a capability of finding food and bring it back to their nest. Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). …”
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6
Embedding Malaysian House Red Ant Behavior into an Ant Colony System
Published 2008“…Problem statement: Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman Problem (TSP). …”
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Citation Index Journal -
7
The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…There have been several scientific investigations in the past several decades on discovering effective and efficient algorithms to providing solutions to the optimization needs of mankind leading to the development of deterministic algorithms that provide exact solutions to optimization problems. …”
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8
A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem
Published 2019“…Specifically, three main phases were involved in developing the hybrid model, which are generating an initial roster, updating the roster through the ACO algorithm, and implementing the hill climbing to further search for a refined solution. …”
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Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…Preliminary computational experiments were conducted on a subset of benchmark data sets as to find the appropriate parameters setting for the developed HACO. The proposed algorithm is tested on two standard benchmark data sets to evaluate the performance and to determine the effectiveness of the algorithm. …”
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10
Enhancing Solutions Of Capacity Vehicle Routing Problem Based On An Improvement Ant Colony System Algorithm
Published 2019“…The paper aims to discover an optimal route for VRP by using Improvement Ant Colony System Algorithm (IACS). Optimal routes are founded based on to decrease the distance and the time for each and every one route which directs to quickest the moving of customers to their locations, also based on developing the CVRP model for optimizing the routing issues. …”
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11
Reducing Iteration Using Candidate List
Published 2008“…Ants are a fascinating creature that demonstrates a capability of finding food and bring it back to their nest. Their ability as a colony to find paths or routes to the food sources has inspired a newly developed algorithm called Dynamic Ant Colony System 3 Level Updates (DACS3). …”
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12
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
13
Ant colony optimization algorithm for rule based classification: Issues and potential
Published 2018“…Potential solutions that may be considered to improve the performance of ACO algorithms in the classification domain were also presented. …”
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14
Improvement DACS3 Searching Performance using Local Search
Published 2009“…The capability of DACS3 is measured based on quality of solution, time taken to reach the solution and algorithm performance. …”
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Conference or Workshop Item -
15
Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…These proposed hybrid algorithms will enhance ACS in terms of exploration mechanism and solution refinement by implementing low and high levels hybridization of ACS, GA, and TS algorithms. …”
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16
FINDING SHORTEST PATH FOR DYNAMIC PUTTING PROBLEM USING ANT COLONY OPTIMISATION
Published 2005“…Specifically. this thesis is intended to develop a system that can display the shortest path by the used of two algorithm in ACO which were Ant System (AS) and Ant Colony System (ACS). …”
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Final Year Project Report / IMRAD -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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18
A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli
Published 2018“…In this research, a hybrid algorithm is developed to seek optimal solutions in order to increase the overproduction of lactate and succinate by gene knockout in E. coli. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…Therefore, in this research, will be use Ant Colony Optimization (ACO) algorithm as an optimize technique that provide a shortest path of defining a successor that is their highest value of criteria. …”
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