Probability Collectives with Feasibility-Based Rule II

This rule is a variation of the Feasibility-based Rule I discussed in Chap. 5 and also allows the objective function and the constraint information to be considered separately.

[1]  Kang Tai,et al.  Target-matching test problem for multiobjective topology optimization using genetic algorithms , 2007 .

[2]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[3]  Tapabrata Ray,et al.  An Evolutionary Algorithm for Constrained Optimization , 2000, GECCO.

[4]  Garret N. Vanderplaats,et al.  Numerical optimization techniques for engineering design , 1999 .

[5]  Jasbir S. Arora,et al.  Introduction to Optimum Design , 1988 .

[6]  Miodrag Potkonjak,et al.  Coverage problems in wireless ad-hoc sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[7]  S. Jayasuriya,et al.  Deployment of Mobile Sensor Networks with Discontinuous Dynamics , 2008 .

[8]  Matt Welsh,et al.  Deploying a wireless sensor network on an active volcano , 2006, IEEE Internet Computing.

[9]  Wang Ping,et al.  A hybrid DE-SQP algorithm with switching procedure for dynamic optimization , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[10]  Guoliang Xing,et al.  Integrated coverage and connectivity configuration in wireless sensor networks , 2003, SenSys '03.

[11]  Steven Fortune,et al.  Voronoi Diagrams and Delaunay Triangulations , 2004, Handbook of Discrete and Computational Geometry, 2nd Ed..

[12]  S. Sitharama Iyengar,et al.  Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks , 2002, IEEE Trans. Computers.

[13]  M. Castillo-Effer,et al.  Wireless sensor networks for flash-flood alerting , 2004, Proceedings of the Fifth IEEE International Caracas Conference on Devices, Circuits and Systems, 2004..

[14]  Gaurav S. Sukhatme,et al.  Constrained coverage for mobile sensor networks , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[15]  K. C. Seow,et al.  MULTIOBJECTIVE DESIGN OPTIMIZATION BY AN EVOLUTIONARY ALGORITHM , 2001 .

[16]  Yong-Chang Jiao,et al.  Modified Differential Evolution for the Integer Programming Problems , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[17]  M. Welsh,et al.  Vital Signs Monitoring and Patient Tracking Over a Wireless Network , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[18]  Donald F. Towsley,et al.  A study of the coverage of large-scale sensor networks , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[19]  Jasbir S. Arora,et al.  4 – Optimum Design Concepts , 2004 .

[20]  Jennifer C. Hou,et al.  Wireless sensor networks , 2004, IEEE Wirel. Commun..

[21]  Thomas F. La Porta,et al.  Movement-Assisted Sensor Deployment , 2006, IEEE Trans. Mob. Comput..

[22]  Guoliang Xing,et al.  Integrated coverage and connectivity configuration for energy conservation in sensor networks , 2005, TOSN.

[23]  Douglas W. Gage,et al.  Command Control for Many-Robot Systems , 1992 .

[24]  Siamak Talatahari,et al.  An improved ant colony optimization for constrained engineering design problems , 2010 .

[25]  Ling Wang,et al.  A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization , 2007, Appl. Math. Comput..

[26]  Parameswaran Ramanathan,et al.  Sensor deployment strategy for target detection , 2002, WSNA '02.

[27]  Koushik Kar,et al.  Low-coordination topologies for redundancy in sensor networks , 2005, MobiHoc '05.

[28]  S. Sitharama Iyengar,et al.  Coding theory framework for target location in distributed sensor networks , 2001, Proceedings International Conference on Information Technology: Coding and Computing.

[29]  George Luger,et al.  Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition) , 2004 .

[30]  Radha Poovendran,et al.  Coverage In Heterogeneous Sensor Networks , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[31]  Dong Xuan,et al.  On Deploying Wireless Sensors to Achieve Both Coverage and Connectivity , 2006, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[32]  Radha Poovendran,et al.  Stochastic coverage in heterogeneous sensor networks , 2006, TOSN.

[33]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[34]  Matt Welsh,et al.  Sensor networks for emergency response: challenges and opportunities , 2004, IEEE Pervasive Computing.

[35]  Chellapilla Patvardhan,et al.  Is stochastic ranking really better than Feasibility Rules for constraint handling in Evolutionary Algorithms? , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[36]  Vassilios E. Theodoracatos,et al.  The optimal packing of arbitrarily-shaped polygons using simulated annealing and polynomial-time cooling schedules , 1995 .

[37]  Dar Yun Chiang,et al.  Improved Simulated Annealing Search for Structural Optimization , 2000 .

[38]  Bruce A. Draper,et al.  A system to place observers on a polyhedral terrain in polynomial time , 2000, Image Vis. Comput..

[39]  Krishnendu Chakrabarty,et al.  Sensor deployment and target localization based on virtual forces , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[40]  Srikrishna Subramanian,et al.  Design optimization of three‐phase energy efficient induction motor using adaptive bacterial foraging algorithm , 2010 .

[41]  Radha Poovendran,et al.  Detection of mobile targets on the plane and in space using heterogeneous sensor networks , 2009, Wirel. Networks.