Ant colony optimization algorithm with pheromone correction strategy for the minimum connected dominating set problem

In this paper an ant colony optimization (ACO) algorithm for the minimum connected dominating set problem (MCDSP) is presented. The MCDSP become increasingly important in recent years due to its applicability to the mobile ad hoc networks (MANETs) and sensor grids. We have implemented a one-step ACO algorithm based on a known simple greedy algorithm that has a significant drawback of being easily trapped in local optima. We have shown that by adding a pheromone correction strategy and dedicating special attention to the initial condition of the ACO algorithm this negative effect can be avoided. Using this approach it is possible to achieve good results without using the complex two-step ACO algorithm previously developed. We have tested our method on standard benchmark data and shown that it is competitive to the existing algorithms. [Projekat Ministarstva nauke Republike Srbije, br. III-44006]

[1]  Thomas Stützle,et al.  A Comparison Between ACO Algorithms for the Set Covering Problem , 2004, ANTS Workshop.

[2]  Christine Solnon,et al.  Searching for Maximum Cliques with Ant Colony Optimization , 2003, EvoWorkshops.

[3]  Michael R. Fellows,et al.  Parameterized approximation of dominating set problems , 2008, Inf. Process. Lett..

[4]  Weili Wu,et al.  A greedy approximation for minimum connected dominating sets , 2004, Theor. Comput. Sci..

[5]  Milan Tuba,et al.  Artificial Bee Colony (ABC) Algorithm for Constrained Optimization Improved with Genetic Operators , 2012 .

[6]  Samir Khuller,et al.  Approximation Algorithms for Connected Dominating Sets , 1996, Algorithmica.

[7]  Weili Wu,et al.  Improving Construction for Connected Dominating Set with Steiner Tree in Wireless Sensor Networks , 2006, J. Glob. Optim..

[8]  Broderick Crawford,et al.  Ant Colonies using Arc Consistency Techniques for the Set Partitioning Problem , 2006, IFIP PPAI.

[9]  Erkki Mäkinen,et al.  A Neural Network Model to Minimize the Connected Dominating Set for Self-Configuration of Wireless Sensor Networks , 2009, IEEE Transactions on Neural Networks.

[10]  M Dorigo,et al.  Ant colonies for the travelling salesman problem. , 1997, Bio Systems.

[11]  Chittaranjan A. Mandal,et al.  An improved greedy construction of minimum connected dominating sets in wireless networks , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[12]  Phen Chiak See,et al.  A new minimum pheromone threshold strategy (MPTS) for max-min ant system , 2009, Appl. Soft Comput..

[13]  Dervis Karaboga,et al.  A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems , 2011, Appl. Soft Comput..

[14]  Ivona Brajevic,et al.  Hybrid Seeker Optimization Algorithm for Global Optimization , 2013 .

[15]  Rolf Drechsler,et al.  Applications of Evolutionary Computing, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Proceedings , 2008, EvoWorkshops.

[16]  Panos M. Pardalos,et al.  A New Algorithm for the Minimum Connected Dominating Set Problem on Ad Hoc Wireless Networks , 2015 .

[17]  Zne-Jung Lee,et al.  Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment , 2008, Appl. Soft Comput..

[18]  Farhad Samadzadegan,et al.  An evolutionary solution for multimodal shortest path problem in metropolises , 2010, Comput. Sci. Inf. Syst..

[19]  Hong Tat Ewe,et al.  AN ENHANCED ANT COLONY OPTIMIZATION METAHEURISTIC FOR THE MINIMUM DOMINATING SET PROBLEM , 2006, Appl. Artif. Intell..

[20]  Qiang Xu,et al.  Clustering Approach for Wireless Sensor Networks Using Spatial Data Correlation and Ant-Colony Optimization , 2009, 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing.

[21]  De-Ren Yang,et al.  Greedy Algorithms for Minimum Connected Dominating Set Problems , 2010 .

[22]  Milan Tuba,et al.  An ant colony optimization algorithm with improved pheromone correction strategy for the minimum weight vertex cover problem , 2011, Appl. Soft Comput..

[23]  Vic Grout,et al.  Metaheuristics for Wireless Network Optimisation , 2007, The Third Advanced International Conference on Telecommunications (AICT'07).

[24]  Jozef Kratica,et al.  A genetic algorithm for the routing and carrier selection problem , 2012, Comput. Sci. Inf. Syst..

[25]  Xiuzhen Cheng,et al.  An Approximation Algorithm for Connected Dominating Set in Ad Hoc Networks , 2004 .

[26]  Haibin Duan,et al.  DEACO: Hybrid Ant Colony Optimization with Differential Evolution , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[27]  Panos M. Pardalos,et al.  A New Heuristic for the Minimum Connected Dominating Set Problem on Ad Hoc Wireless Networks , 2004 .

[28]  Quan-Ke Pan,et al.  A hybrid variable neighborhood search algorithm for solving multi-objective flexible job shop problems , 2010, Comput. Sci. Inf. Syst..

[29]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[30]  Sibiu,et al.  An Object-Oriented Framework with Corresponding Graphical User Interface for Developing Ant Colony Optimization Based Algorithms , 2008 .

[31]  M. Tuba,et al.  Ant colony optimization applied to minimum weight dominating set problem , 2010 .

[32]  Chittaranjan A. Mandal,et al.  Minimum Connected Dominating Set Using a Collaborative Cover Heuristic for Ad Hoc Sensor Networks , 2010, IEEE Transactions on Parallel and Distributed Systems.