A survey: Ant Colony Optimization based recent research and implementation on several engineering domain

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.

[1]  Gianluca Reali,et al.  On ant routing algorithms in ad hoc networks with critical connectivity , 2008, Ad Hoc Networks.

[2]  Chandra Mohan,et al.  Improving Network Performance using ACO Based Redundant Link Avoidance Algorithm , 2010 .

[3]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[4]  Bart Baesens,et al.  Building comprehensible customer churn prediction models with advanced rule induction techniques , 2011, Expert Syst. Appl..

[5]  Nam Pham Improving network performance in wireless networks , 2007 .

[6]  B. Chandra Mohan,et al.  A Data Mining Approach for Predicting Reliable Path for Congestion Free Routing Using Self-motivated Neural Network , 2008, Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[7]  Komarudin,et al.  Applying Ant System for solving Unequal Area Facility Layout Problems , 2010, Eur. J. Oper. Res..

[8]  Víctor Yepes,et al.  Heuristic optimization of RC bridge piers with rectangular hollow sections , 2010 .

[9]  B. Chandra A Data Mining Approach for Predicting Reliable Path for Congestion Free Routing using Self-Motivated Neural Network , 2008 .

[10]  J. Deneubourg,et al.  The self-organizing exploratory pattern of the argentine ant , 1990, Journal of Insect Behavior.

[11]  B. Chandra Mohan,et al.  Energy Aware and Energy Efficient Routing Protocol for Adhoc Network Using Restructured Artificial Bee Colony System , 2011, HPAGC.

[12]  Wang Chen,et al.  An efficient hybrid algorithm for resource-constrained project scheduling , 2010, Inf. Sci..

[13]  Taher Niknam,et al.  A practical algorithm for optimal operation management of distribution network including fuel cell power plants , 2010 .

[14]  Sergej Jakovlev,et al.  Comparison of Two Heuristic Approaches for Solving the production Scheduling Problem , 2011, Inf. Technol. Control..

[15]  J. Deneubourg,et al.  Self-organized shortcuts in the Argentine ant , 1989, Naturwissenschaften.

[16]  Lixiang Li,et al.  A multi-objective chaotic ant swarm optimization for environmental/economic dispatch , 2010 .

[17]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[18]  Elena Navarro,et al.  An emotionally biased ant colony algorithm for pathfinding in games , 2010, Expert Syst. Appl..

[19]  Omar M. Sallabi,et al.  A Novel Approach for Combining Genetic and Simulated Annealing Algorithms , 2011 .

[20]  Ch. Venkateswarlu,et al.  Mathematical and kinetic modeling of biofilm reactor based on ant colony optimization , 2010 .

[21]  B. Chandra Mohan,et al.  Survey on Recent Research and Implementation of Ant Colony Optimization in Various Engineering Applications , 2011, Int. J. Comput. Intell. Syst..

[22]  Nor Ashidi Mat Isa,et al.  Color image segmentation using histogram thresholding - Fuzzy C-means hybrid approach , 2011, Pattern Recognit..

[23]  Jun Zhang,et al.  Optimizing Discounted Cash Flows in Project Scheduling—An Ant Colony Optimization Approach , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[24]  Rolf H. Möhring,et al.  Resource-constrained project scheduling: Notation, classification, models, and methods , 1999, Eur. J. Oper. Res..

[25]  Oscar C. Au,et al.  An adaptive unsupervised approach toward pixel clustering and color image segmentation , 2010, Pattern Recognit..

[26]  Sheng Liu,et al.  Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm , 2010, Int. J. Comput. Intell. Syst..

[27]  J. Deneubourg,et al.  Self-organization mechanisms in ant societies. I. Trail recruitment to newly discovered food sources , 1987 .

[28]  Steven Schockaert,et al.  Generating approximate region boundaries from heterogeneous spatial information: An evolutionary approach , 2011, Inf. Sci..

[29]  Peng Wang,et al.  A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems , 2010, Appl. Soft Comput..

[30]  Muddassar Farooq,et al.  Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions , 2011, Inf. Sci..

[31]  Lionel Amodeo,et al.  Bi-Objective Ant Colony Optimization approach to optimize production and maintenance scheduling , 2010, Comput. Oper. Res..

[32]  Frank Neumann,et al.  Ant Colony Optimization and the minimum spanning tree problem , 2010, Theor. Comput. Sci..

[33]  Jihong Zhu,et al.  Ant estimator with application to target tracking , 2010, Signal Process..

[34]  Jing Tian,et al.  Wavelet-Based Image Interpolation Using a Three-Component Exponential Mixture Model , 2008, 2008 Congress on Image and Signal Processing.

[35]  B. Chandra Mohan,et al.  Reliable Barrier-Free Services (RBS) for Heterogeneous Next Generation Network , 2011 .

[36]  Hsin-Yun Lee,et al.  Decision support for the maintenance management of green areas , 2010, Expert Syst. Appl..

[37]  Ali Maroosi,et al.  A new clustering algorithm based on hybrid global optimizationbased on a dynamical systems approach algorithm , 2010, Expert Syst. Appl..

[38]  Ahmad Alibabaee,et al.  Application of the ant colony search algorithm to reactive power pricing in an open electricity market , 2009 .

[39]  Francisco Herrera,et al.  Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAP , 2010, Expert Syst. Appl..

[40]  Kwang Mong Sim,et al.  Ant colony optimization for routing and load-balancing: survey and new directions , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[41]  Thomas Stützle,et al.  An analysis of communication policies for homogeneous multi-colony ACO algorithms , 2010, Inf. Sci..

[42]  B. Chandra Mohan,et al.  Priority and compound rule based routing using ant colony optimization , 2011, Int. J. Hybrid Intell. Syst..

[43]  Manuel López-Ibáñez,et al.  Beam-ACO for the travelling salesman problem with time windows , 2010, Comput. Oper. Res..

[44]  Thomas Stützle,et al.  Ant Colony Optimization Theory , 2004 .

[45]  Mohammad S. Obaidat,et al.  A low-overhead fault-tolerant routing algorithm for mobile ad hoc networks: A scheme and its simulation analysis , 2010, Simul. Model. Pract. Theory.

[46]  Luca Maria Gambardella,et al.  A new approach for heuristics-guided search in the In-Core Fuel Management Optimization , 2010 .

[47]  Waree Kongprawechnon,et al.  Ant colony optimisation for economic dispatch problem with non-smooth cost functions , 2010 .

[48]  Erik Demeulemeester,et al.  Resource-constrained project scheduling: A survey of recent developments , 1998, Comput. Oper. Res..

[49]  Moacir Godinho Filho,et al.  A software model to prototype ant colony optimization algorithms , 2011, Expert Syst. Appl..