Resource-constrained project scheduling: a survey of recent developments
Computers and Operations Research
An efficient hybrid algorithm for resource-constrained project scheduling
Information Sciences: an International Journal
Ant estimator with application to target tracking
Signal Processing
Beam-ACO for the travelling salesman problem with time windows
Computers and Operations Research
Bi-Objective Ant Colony Optimization approach to optimize production and maintenance scheduling
Computers and Operations Research
Heuristic optimization of RC bridge piers with rectangular hollow sections
Computers and Structures
Decision support for the maintenance management of green areas
Expert Systems with Applications: An International Journal
A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems
Applied Soft Computing
Expert Systems with Applications: An International Journal
An emotionally biased ant colony algorithm for pathfinding in games
Expert Systems with Applications: An International Journal
An analysis of communication policies for homogeneous multi-colony ACO algorithms
Information Sciences: an International Journal
Ant Colony Optimization and the minimum spanning tree problem
Theoretical Computer Science
Expert Systems with Applications: An International Journal
Optimizing discounted cash flows in project scheduling: an ant colony optimization approach
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A software model to prototype ant colony optimization algorithms
Expert Systems with Applications: An International Journal
Building comprehensible customer churn prediction models with advanced rule induction techniques
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions
Information Sciences: an International Journal
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ant colony optimization for routing and load-balancing: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Learning fuzzy cognitive maps from data by ant colony optimization
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
Bio-inspired optimisation approach for data association in target tracking
International Journal of Wireless and Mobile Computing
Multi-satellite control resource scheduling based on ant colony optimization
Expert Systems with Applications: An International Journal
Software Survey: Distributed job scheduling based on Swarm Intelligence: A survey
Computers and Electrical Engineering
Ant colony optimisation for vehicle traffic systems: applications and challenges
International Journal of Bio-Inspired Computation
Hi-index | 12.05 |
Ant Colony Optimization (ACO) is a Swarm Intelligence technique which inspired from the foraging behaviour of real ant colonies. The ants deposit pheromone on the ground in order to mark the route for identification of their routes from the nest to food that should be followed by other members of the colony. This ACO exploits an optimization mechanism for solving discrete optimization problems in various engineering domain. From the early nineties, when the first Ant Colony Optimization algorithm was proposed, ACO attracted the attention of increasing numbers of researchers and many successful applications are now available. Moreover, a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO. This paper review varies recent research and implementation of ACO, and proposed a modified ACO model which is applied for network routing problem and compared with existing traditional routing algorithms.