Evolutionary optimization as applied to inverse scattering problems

Inverse Problems

Volumn 25, Issue 12, 2009, Pages

  Rocca, P ^a   Benedetti, M ^a   Donelli, M ^a   Franceschini, D ^a   Massa, A ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

APRIORI; BIOMEDICAL IMAGING; CONDUCTING OBJECTS; DOMAIN KNOWLEDGE; EVOLUTION PROCESS; EVOLUTIONARY APPROACH; EVOLUTIONARY OPTIMIZATIONS; GENERAL DESCRIPTION; HYBRID IMPLEMENTATION; INVERSE SCATTERING PROBLEMS; LOCAL SEARCH TECHNIQUES; OPEN PROBLEMS; OPTIMIZATION PROCESS; POPULATION-BASED OPTIMIZATION; SHAPE RECONSTRUCTION; STOCHASTIC PROCESS; SUB-SURFACES; UNKNOWN OBJECTS;

DIELECTRIC PROPERTIES; EVOLUTIONARY ALGORITHMS; MATHEMATICAL OPERATORS; OPTIMIZATION; RANDOM PROCESSES; SCATTERING; SENSITIVITY ANALYSIS; STOCHASTIC SYSTEMS;

INVERSE PROBLEMS;

EID: 72049093274     PISSN: 02665611     EISSN: 13616420     Source Type: Journal    
DOI: 10.1088/0266-5611/25/12/123003     Document Type: Review

References (175)

1. Ali M M and Torn A 2004 Population set based global optimization algorithms: some modifications and numerical studies Comput. Oper. Res. 31 1703-25
2. Arkadan A A, Sareen T and Subramaniam S 1994 Genetic algorithms for nondestructive testing in crack identification IEEE Trans. Magn. 30 4320-2
3. Asoh H and Muhlenbein H 1994 On the mean convergence time of evolutionary algorithms without selection and mutation Parallel Problem Solving from Nature III. Proc. Int. Conf. Evol. Comput. (Lecture Notes in Computer Science vol 866) pp 88-97
4. Back T 1994 Selective pressure in evolutionary algorithms: a characterization of selection mechanisms Proc. 1st IEEE Conf. on Evolutionary Computation (Piscataway, NJ: IEEE Press) pp 57-62
5. Barker A L and Martin W N 2000 Dynamics of a distance-based population diversity measure Proc. 2000 IEEE Congress on Evolutionary Computation (16-19 July 2000) vol 2 pp 1002-9
6. Bréard A, Perrusson G and Lesselier D 2008 Hybrid differential evolution and retrieval of buried spheres in subsoil IEEE Geosci. Remote Sens. Lett. 5 788-92
7. Benedetti M, Donelli M, Franceschini G, Pastorino M and Massa A 2005 Effective exploitation of the a priori information through a microwave imaging procedure based on the SMW for NDE/NDT applications IEEE Trans. Geosci. Remote Sens. 43 2584-92
8. Benedetti M, Donelli M and Massa A 2007 Multicrack detection in two-dimensional structures by means of GA-based strategies IEEE Trans. Antennas Propag. 55 205-15
9. Benedetti M, Franceschini G, Azaro R and Massa A 2007 A numerical assessment of the reconstruction effectiveness of the integrated GA-based multicrack strategy IEEE Antennas Wirel. Propag. Lett. 6 271-4
10. Bertero M and Boccacci P 1998 Introduction to Inverse Problems in Imaging (Bristol: Institute of Physics Publishing)
11. Bertoni A and Dorigo M 1993 Implicit parallelism in genetic algorithms Artif. Intell. 61 307-14
12. Bilchev B and Parmee I C 1995 The ant colony metaphor for searching continuous design spaces Proc. AISB Workshop Evol. Comput. (Lecture Notes in Computer Science vol 993) pp 25-39
13. Blum C and Dorigo M 2005 Search bias in ant colony optimization: on the role of competition-balanced systems IEEE Trans. Evol. Comput. 9 159-74
14. Blum C, Blesa Aguilera M J, Roli A and Sampels M 2008 Hybrid Metaheuristics: An Emerging Approach to Optimization (Berlin: Springer)
15. Boeringer D W and Werner D H 2004 Particle swarm optimization versus genetic algorithms for phased array synthesis IEEE Trans. Antennas Propag. 52 771-9
16. Bonabeau E, Dorigo M and Theraulaz G 1999 Swarm Intelligence: From Natural to Artificial Systems (New York: Oxford Univesity Press)
17. Booker L B, Goldberg D E and Holland J H 1989 Classifier systems and genetic algorithms Artif. Intell. 40 235-82
18. Bort E, Franceschini G, Massa A and Rocca P 2005 Improving the effectiveness of GA-based approaches to microwave imaging through an innovative parabolic crossover IEEE Antennas Wirel. Propag. Lett. 4 138-42
19. Bramlette M F and Bouchard E E 1991 Genetic algorithms in parametric design of aircraft Handbook of Genetic Algorithms (New York: Van Nostrand Reinhold) chapter 10 pp 109-23
20. Brignone M, Bozza G, Randazzo A, Piana M and Pastorino M 2008 A hybrid approach to 3D microwave imaging by using linear sampling and ACO IEEE Trans. Antennas Propag. 56 3224-32
21. Cantu-Paz E 1995 A summary of research on parallel genetic algorithms Tech. Rep. 95007 (Illinois: Illinois Genetic Algorithms Laboratory)
22. Caorsi S, Massa A, Pastorino M and Righini F 2000 Crack detection in lossy two-dimensional structures by means of a microwave imaging approach Int. J. Appl. Electromagn. Mech. 11 233-44
23. Caorsi S and Pastorino M 2000 Two-dimensional microwave imaging approach based on a genetic algorithm IEEE Trans. Antennas Propag. 48 370-3
24. Caorsi S, Massa A and Pastorino M 2000 A computational technique based on a real-coded genetic algorithm for microwave imaging purposes IEEE Trans. Geosci. Remote Sens. 38 1697-708 (Pubitemid 30910773)
25. Caorsi S, Costa A and Pastorino M 2001 Microwave imaging within the second-order born approximation: stochastic optimization by a genetic algorithm IEEE Trans. Antennas Propag. 49 22-31
26. Caorsi S, Massa A and Pastorino M 2001 A crack identification microwave procedure based on a genetic algorithm for nondestructive testing IEEE Trans. Antennas Propag. 49 1812-20
27. Caorsi S, Massa A, Pastorino M, Raffetto M and Randazzo A 2003 Detection of buried inhomogeneous elliptic cylinders by a memetic algorithm IEEE Trans. Antennas Propag. 51 2878-84
28. Caorsi S, Massa A, Pastorino M and Randazzo A 2003 Electromagnetic detection of dielectric scatterers using phaseless synthetic and real data and the memetic algorithm IEEE Trans. Geosci. Remote Sens. 41 2745-53
29. Caorsi S, Massa A, Pastorino M and Rosani A 2004 Microwave medical imaging: potentialities and limitations of a stochastic optimization technique IEEE Trans. Microwave Theory Tech. 52 1909-16
30. Caorsi S, Massa A, Pastorino M and Donelli M 2004 Improved microwave imaging procedure for nondestructive evaluations of two-dimensional structures IEEE Trans. Antennas Propag. 52 1386-97
31. Caorsi S, Donelli M, Lommi A and Massa A 2004 Location and imaging of two-dimensional scatterers by using a particle swarm algorithm J. Electromagn. Waves Appl. 18 481-94
32. Caorsi S, Massa A, Pastorino M, Raffetto M and Randazzo A 2004 Microwave imaging of cylindrical inhomogeneities based on an analytical forward solver and multiple illuminations Proc. 2004 IEEE Int. Workshop on Imaging Systems and Techniques (Stresa, Italy) 100-5
33. Chakraborty U K 2008 Advances in Differential Evolution (Berlin: Springer)
34. Chen X, O'Neill K, Barrowes B E, Grzegorczyk T M and Kong J A 2004 Application of a spheroidal-mode approach and a differential evolution algorithm for inversion of magneto-quasistatic data in UXO discrimination Inverse Problems 20 27-40
35. Chew W C 1995 Waves and Fields in Inhomogeneous Media (New York: IEEE Press)
36. Chew W C, Jin J-M, Michielssen E and Song J 2001 Fast and Efficient Algorithms in Computational Electromagnetics (Boston, MA: Artech House Publishers)
37. Chien W and Chiu C-C 2003 Using NU-SSGA to reduce the searching time in inverse problem of a buried metallic object IEEE Trans. Antennas Propag. 53 3128-34
38. Chien W and Chiu C-C 2005 Using NU-SSGA to reduce the searching time in inverse problem of a buried metallic object IEEE Trans. Antennas Propag. 53 3128-34
39. Chiu C-C and Liu P-T 1996 Image reconstruction of a perfectly conducting cylinder by the genetic algorithm IEE Proc. Microw. Antennas Propag. 143 249-53
40. Chiu C C and Liu P T 1998 Electromagnetic transverse electric-wave inverse scattering of a conductor by the genetic algorithm Int. J. Imaging Syst. Technol. 9 388-94
41. Chiu C-C and Chen W-T 2000 Electromagnetic imaging for an imperfectly conducting cylinder by the genetic algorithm IEEE Trans. Microwave Theory Tech. 48 1901-5
42. Clerc M and Kennedy J 2002 The particle swarm-explosion, stability, and convergence in a multidimensional complex space IEEE Trans. Evol. Comput. 6 58-73
43. Coello C, Van Veldhuizen D A and Lamont G B 2007 Evolutionary Algorithms for Solving Multi-Objective Problems 2nd edn (New York: Springer)
44. Collaro A, Franceschetti G, Palmieri F and Ferreiro M S 1998 Phase unwrapping by means of genetic algorithms J. Opt. Soc. Am. A 15 407-18
45. Costa D and Hertz A 1997 Ants can colour graphs J. Oper. Res. Soc. 48 295-305
46. Dawkins R 1976 The Selfish Gene (New York: Oxford University Press)
47. De Jong K A 1975 An analysis of the behavior of a class of genetic adaptive systems PhD Dissertation University of Michigan
48. De Jong K A and Spears W M 1992 A formal analysis of the role of multi-point crossover in genetic algorithms Ann. Math. Artif. Intell. 5 1-26
49. Donelli M and Massa A 2005 Computational approach based on a particle swarm optimizer for microwave imaging of two-dimensional dielectric scatterers IEEE Trans. Microw. Theory Tech. 53 1761-76
50. Donelli M, Franceschini G, Martini A and Massa A 2006 An integrated multiscaling strategy based on a particle swarm algorithm for inverse scattering problems IEEE Trans. Geosci. Remote Sens. 44 298-312
51. Donelli M, Franceschini D, Rocca P and Massa A 2009 Three-dimensional microwave imaging problems solved through an efficient multiscaling particle swarm optimization IEEE Trans. Geosci. Remote Sens. 47 1467-81
52. Dorigo M, Maniezzo V and Colorni A 1996 Ant system: optimization by a colony of cooperating agents IEEE Trans. Syst. Man Cybern. B 26 29-41
53. Dorigo M and Gambarella L M 1997 Ant colony system: a cooperative learning approach to the traveling salesman problem IEEE Trans. Evol. Comput. 1 53-66
54. Dorigo M and Stutzle T 2004 Ant Colony Optimization (Cambridge, MA: MIT Press)
55. Dorigo M and Blum C 2005 Ant colony optimization theory: a survey Theor. Comput. Sci. 344 243-78
56. Eberhart R C and Shi Y 2000 Comparing inertia weights and constriction factors in particle swarm optimization Proc. Congr. Evolutionary Computation (Piscataway, NJ) vol 1 pp 84-88
57. Eiben A E, Aarts E H L and Van Hee K M 1991 Global convergence of genetic algorithms: a Markov chain analysis Parallel Problem Solving from Nature ed H-P Schwefel and R Manner (Berlin: Springer) pp 4-12
58. El-Gallad A I, El-Hawary M, Sallam A A and Kalas A I 2001 Swarm intelligence for hybrid cost dispatch problem Proc. Can. Electrical and Computer Engineering Conf. vol 2 pp 753-7
59. Ermoliev Y and Wets R J B 1988 Numerical Techniques for Stochastic Optimization (New York: Springer)
60. Fan H-Y and Lampinen J 2003 A trigonometric mutation operation to differential evolution J. Global Optim. 27 105-29
61. Forrest S 1993 Genetic algorithms: principles of natural selection applied to computation Science 261 872-8
62. Franceschini G, Donelli M, Azaro R and Massa A 2006 Inversion of phaseless total field data using a two-step strategy based on the iterative multiscaling approach IEEE Trans. Geosci. Remote Sens. 44 3527-39
63. Gamperle R, Muller S D and Koumoutsakos P 2002 A parameter study for differential evolution WSEAS, Int. Conf. on Advances in Intelligent Systems, Fuzzy Systems, Evolutionary Computation ed A Grmela and N Mastorakis (WSEAS Press) pp 293-8
64. Garnier S, Gautrais J and Theraulaz G 2007 The biological principles of swarm intelligence Swarm Intell. 1 3-31
65. Ge D B, Yan Y B, Shi S Y and Nie X C 1997 Genetic algorithm applied to inverse scattering: two examples Proc. Asia Pacific Microwave Conf. 689-92
66. Genovesi S, Salerno E, Monorchio A and Manara G 2005 A permittivity range profile reconstruction technique for multilayered structures by a line process-augmented genetic algorithm Proc. 2005 IEEE AP-S Int. Symp. (Washington DC, USA, 20-25 Jun. 2005) 216-9
67. Goldberg D E and Segrest P 1987 Finite Markov chain analysis of genetic algorithms Proc. 2nd Int. Conf. Genetic Algorithms 1-8
68. Goldberg D E 1987 Simple genetic algorithms and the minimal deceptive problem Genetic Algorithms and Simulated Annealing ed L Davis (London, UK: Pitman) pp 74-88
69. Goldberg D E 1989 Genetic Algorithms in Search, Optimization, and Machine Learning (Boston, MA: Addison-Wesley)
70. Goonatilake S and Treleaven P 1995 Intelligent Systems for Finance and Business (Chichester: Wiley)
71. Grassé P P 1959 La reconstruction du nid et les coordinations inter-individuelles chez Bellicositermes Natalensis et Cubitermes sp. La théorie de la stigmergie: essai d'interprétation du comportement des termites constructeurs Insectes Sociaux 6 41-81
72. Gutjahr W J 2000 A graph-based ant system and its convergence Future Gener. Comput. Syst. 16 873-88
73. Gutjahr W J 2002 ACO algorithms with guaranteed convergence to the optimal solution Inform. Process. Lett. 82 145-53
74. Harrald P G 1996 Evolutionary algorithms and economic models: a view Proc. 5th Annu. Conf. on Evolutionary Programming (Cambridge, MA: MIT Press) pp 3-7
75. Holland H 1975 Adaptation in Natural and Artificial Systems (Ann Arbor, MI: University of Michigan Press)
76. Haupt R L 1995 An introduction to genetic algorithms for electromagnetics IEEE Antennas Propag. Magn. 37 7-15
77. Holland J H 1992 Genetic algorithms Sci. Am. 267 66-72
78. Horn J 1993 Finite Markov chain analysis of genetic algorithms with niching Proc. 5th Int. Conf. Genetic Algorithms pp 110-7
79. Huang T and Mohan A S 2004 Microwave imaging of perfect electrically conducting cylinder by micro-genetic algorithm Proc. 2004 IEEE AP-S Int. Symp. (Monterey, CA, USA) pp 221-4
80. Huang T and Mohan A S 2005 Application of particle swarm optimization for microwave imaging of lossy dielectric objects Proc. 2005 IEEE AP-S Int. Symp. (Washington DC, USA, 20-25 June, 2005) pp 852-5
81. Huang T and Mohan A S 2005 A hybrid boundary condition for robust particle swarm optimization IEEE Antennas Wirel. Propag. Lett. 4 112-7
82. Huang T and Mohan A S 2005 Significance of neighborhood topologies for the reconstruction of microwave images using particle swarm optimization Proc. APMC-2005 Asia-Pacific Microwave Conference (4-7 December 2005, Suzhou, China) vol 1
83. Huang T and Mohan A S 2007 A microparticle swarm optimizer for the reconstruction of microwave images IEEE Trans. Antennas Propag. 55 568-76
84. Kehyayan C, Mansour N and Khachfe H Evolutionary algorithm for protein structure prediction Proc. ICACTE '08 Int. Conf. Advanced Computer Theory and Engineering (25-27 September 2008, Cairo, Egypt) pp 925-9
85. Kennedy J and Eberhart R 1995 Particle swarm optimization Proc. 1995 IEEE Intern. Conf. Neural Networks (Piscataway, NJ, USA) pp 1942-8
86. Kennedy J and Eberhart R C 1997 A discrete binary version of the particle swarm algorithm Proc. World Multiconf. Syst., Cyber. Informatics (Piscataway, NJ, USA) pp 4104-9
87. Kennedy J, Eberhart R C and Shi Y 2001 Swarm Intelligence (San Francisco, CA: Morgan Kaufmann)
88. Koza J R 1992 Genetic Programming: On the Programming of Computers by Means of Natural Selection (Cambridge, MA: MIT Press)
89. Janikow C Z and Michalewicz Z 1991 An experimental comparison of binary and floating point representations in genetic algorithms Proc. 4th Int. Conf. Genetic Algorithms (San Diego, CA, USA, July 1991) pp 31-6
90. Johnson J M and Ramat-Samii Y 1997 Genetic algorithms in engineering electromagnetics IEEE Antennas Propag. Magn. 39 7-21
91. Johnston R L 2004 Applications of Evolutionary Computation in Chemistry (Berlin: Springer)
92. Lewandowski A and Volkovich V L 1991 Multiobjective Problems of Mathematical Programming Proc. Int. Conf. Multiobjective Problems of Mathematical Programming (Yalta, USSR, 26 October-2 November 1988) (Berlin: Spinger)
93. Li F, Chen X and Huang K 2008 Microwave imaging a buried object by the GA and using the s11 parameter Prog. Electromagn. Res. 85 289-302
94. Liu J and Lampinen J 2002 On setting the control parameter of the differential evolution method Proc. 8th Int. Conf. Soft Computing (MENDEL 2002) (Brno, Czech Republic) pp 11-8
95. Maniezzo V 1999 Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem INFORMS J. Comput vol 11 pp 358-69
96. Marklein R, Balasubramanian K, Qing A and Langenberg K J 2001 Linear and nonlinear iterative scalar inversion of multi-frequency multi-bistatic experimental electromagnetic scattering data Inverse Problems 17 1597-610
97. Massa A, Pastorino M and Randazzo A 2004 Reconstruction of two-dimensional buried objects by a differential evolution method Inverse Problems 20 135-50
98. Massa A, Franceschini D, Franceschini G, Pastorino M, Raffetto M and Donelli M 2005 Parallel GA-based approach for microwave imaging applications IEEE Trans. Antennas Propag. 53 3118-27
99. Mendes R, Kennedy J and Neves J 2003 Watch thy neighbor or how the swarm can learn from its environment Proc. IEEE Swarm Intell. Symp. pp 88-94
100. Meng Z Q, Takenaka T and Tanaka T 1999 Image reconstruction of two-dimensional impenetrable objects using genetic algorithm J. Electromagn. Waves Appl. 13 95-118
101. Meng Z-Q, Takenaka T and He S 2000 A genetic algorithm with an adaptive chromosome structure for reconstruction of radome parameters using a Gaussian beam Microw. Opt. Technol. Lett. 25 323-7
102. Merkle D and Middendorf M 2003 Ant colony optimization with global pheromone evaluation for scheduling a single machine Appl. Intell. 18 105-11
103. Merz P and Freisleben B 2000 Fitness landscape analysis and memetic algorithms for the quadratic assignment problem IEEE Trans. Evol. Comput. 4 337-52
104. Meuleau N and Dorigo M 2002 Ant colony optimization and stochastic gradient descent Artif. Life 8 103-21
105. Michalski K A 2000 Electromagnetic imaging of circular-cylindrical conductors and tunnels using a differential evolution algorithm Microw. Opt. Technol. Lett. 27 330-4
106. Michalski K A 2001 Electromagnetic imaging of elliptical-cylindrical conductors and tunnels using a differential evolution algorithm Microw. Opt. Technol. Lett. 28 164-9
107. Mikki S M and Kishk A A 2007 Physical theory for particle swarm optimization Prog. Electromagn. Wave Res. 75 171-207
108. Morabito A F, Catapano I, D'Urso M, Crocco L and Isernia T 2009 A stepwise approach for quantitative 3D imaging: rationale and experimental results Proc. 2009 IEEE AP-S Int. Symp. (Charleston, SC) p 112.1
109. Moscato P 1989 On evolution, search, optimization, GAs and martial arts: optimization towards memetic algorithms California Inst. Technol., Pasadena, CA, Tech. Rep. Caltech Concurrent Comput. Prog. Rep. 826
110. Niwa T and Tanaka M 1995 On the mean convergence time for simple genetic algorithms Proc. 1995 IEEE Int. Conf. Evolutionary Computation vol 1 pp 373-7
111. Nocedal J and Wright S J 1999 Numerical Optimization (New York: Springer)
112. Ozcan E and Mohan C K 1999 Particle swarm optimization: surfing the waves Proc. 1999 Congr. Evolutionary Computation (Washington, DC, July 1999) pp 1939-44
113. Pareto V 1986 Cours d'Economie Politique (Lausanne: F. Rouge)
114. Park C S and Jeong B S 1999 Reconstruction of a high contrast and large object by using the hybrid algorithm combining a Levenberg-marquardt algorithm and a genetic algorithm IEEE Trans. Magn. 35 1582-5
115. Pastorino M, Massa A and Caorsi S 2000 A microwave inverse scattering technique for image reconstruction based on a genetic algorithm IEEE Trans. Instrum. Meas. 49 573-8 (Pubitemid 30902115)
116. Pastorino M, Caorsi S and Massa A 2002 A global optimization technique for microwave nondestructive evaluation IEEE Trans. Instrum. Meas. 51 666-73
117. Pastorino M, Caorsi S, Massa A and Randazzo A 2004 Reconstruction algorithms for electromagnetic imaging IEEE Trans. Instrum. Meas. 53 692-9
118. Pastorino M 2007 Stochastic optimization methods applied to microwave imaging: a review IEEE Trans. Antennas Propag. 55 538-48
119. Polak E 1971 Computational Methods in Optimization (New York: Academic)
120. Poli R, Kennedy J and Blackwell T 2007 Particle swarm optimization-an overview Swarm Intell. 1 33-57
121. Price K V, Storn R M and Lampinen J A 2005 Differential Evolution: A Practical Approach to Global Optimization (Berlin: Springer)
122. Qi X and Palmieri F 1994 Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space: part I. Basic properties of selection and mutation IEEE Trans. Neural Netw. 5 102-19
123. Qi X and Palmieri F 1994 Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space: part II. Analysis of the diversification role of crossover IEEE Trans. Neural Netw. 5 120-9
124. Qing A, Lee C K and Jen L 1999 Microwave imaging of parallel perfectly conducting cylinders using real-coded genetic algorithm J. Electromagn. Waves Appl. 13 1121-43
125. Qing A and Lee C K 1999 Microwave imaging of a perfectly conducting cylinder using a real-coded genetic algorithm Proc. IEE Microw. Antennas Propag. 146 421-5 (Pubitemid 32212582)
126. Qing A and Lee C K 2000 Microwave imaging of parallel perfectly conducting cylinders using real-coded genetic algorithm coupled with Newton-Kantorovitch method J. Electromagn. Waves Appl. 14 799-800
127. Qing A, Lee C K and Jen L 2001 Electromagnetic inverse scattering of two-dimensional perfectly conducting objects by real-coded genetic algorithm IEEE Trans. Geosci. Remote Sens. 39 665-76
128. Qing A 2001 An experimental study on electromagnetic inverse scattering of a perfectly conducting cylinder by using the real-coded genetic algorithm Microw. Opt. Technol. Lett. 30 315-20
129. Qing A 2002 Electromagnetic imaging of two-dimensional perfectly conducting cylinders with transverse electric scattered field IEEE Trans. Antennas Propag. 50 1786-94
130. Qing A 2003 Electromagnetic inverse scattering of multiple two-dimensional perfectly conducting objects by the differential evolution strategy IEEE Trans. Antennas Propag. 51 1251-62
131. Qing A 2004 Electromagnetic inverse scattering of multiple perfectly conducting cylinders by differential evolution strategy with individuals in groups (GDES) IEEE Trans. Antennas. Propag. 52 1223-9
132. Qing A 2006 Dynamic differential evolution strategy and applications in electromagnetic inverse scattering problems IEEE Trans. Geosci. Remote Sens. 44 116-25
133. Qing A 2007 A parametric study on differential evolution based on benchmark electromagnetic inverse scattering problem Proc. 2007 IEEE Congress Evol. Comput. (CEC 2007) (Tokyo, Japan) pp 1904-9
134. Rekanos I T 2008 Shape reconstruction of a perfectly conducting scatterer using differential evolution and particle swarm optimization IEEE Trans. Geosci. Remote Sens. 46 1967-74
135. Reimann M, Doerner K and Hartl R F 2004 D-ants: savings based ants divide and conquer the vehicle routing problem Comput. Oper. Res. 31 563-91
136. Reimann M 2007 Progress in Complex Systems Optimization (Berlin: Springer)
137. Richmond J H 1965 Scattering by a dielectric cylinder of arbitrary cross-section shape IEEE Trans. Antennas Propag. 13 334-41
138. Robinson J and Rahmat-Samii Y 2004 Particle swarm optimization in electromagnetics IEEE Trans. Antennas Propag. 52 397-407
139. Rudolph G 1994 Convergence analysis of canonical genetic algorithms IEEE Trans. Neural Netw. 5 96-101
140. Sabouni A, Xu M, Noghanian S, Thulasiraman P and Pistorius S 2007 Efficient microwave breast imaging technique using parallel finite difference time domain and parallel genetic algorithms Proc. 2007 IEEE AP-S Int. Symp. (Albuquerque, NM) pp 2176-9
141. Saeedfar A and Barkeshli K 2006 Shape reconstruction of three-dimensional conducting curved plates using physical optics, NURBS modeling, and genetic algorithm IEEE Trans. Antennas Propag. 54 2497-507
142. Schaffer J D 1984 Multiple objective optimization with vector evaluated genetic algorithms PhD Dissertation Vanderbilt University, Nashville, TN
143. Schaffer J D 1985 Multiple objective optimization with vector evaluated genetic algorithms Proc. 1st Int. Conf. Genetic Algorithms (Hillsdale, NJ, Lawrence Erlbaum) pp 93-100
144. Schneider J J and Kirkpatrick S 2006 Stochastic Optimization (Berlin: Springer)
145. Semnani A and Kamyab M 2007 An enhanced method for inverse scattering problems using Fourier series expansion in conjunction with FDTD and PSO Prog. Electromagn. Res. 76 45-64
146. Shi Y and Eberhart R C 1998 A modified particle swarm optimizer Proc. 1998 IEEE Int. Conf. Evol. Comput. (Piscataway, NJ: IEEE Press) pp 69-73
147. Shi Y and Eberhart R C 1999 Empirical study of particle swarm optimization Proc. Congr. Evolutionary Computation (DC) pp 1945-50
148. Socha K 2004 ACO for continuous and mixed-variable optimization Proc. 4th Int. Workshop Ant Colony Optim. Swarm Intell. (ANTS'2004) (Brussels, Belgium, 5-8 September 2004)
149. Socha K and Blum C 2007 An ant colony optimization algorithm for continuous optimization: application to feed-forward neural network training Neural Comput. Appl. 16 235-47
150. Storn R and Price K 1995 Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces Technical Report TR-95-012 (Berkeley, CA: International Comput. Science Inst.)
151. Storn R and Price K 1997 Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces J. Global Optim. 11 341-59
152. Stutzle T and Dorigo M 2002 A short convergence proof for a class of ant colony optimization algorithms IEEE Trans. Evol. Comput. 6 358-65
153. Suzuki J 1993 A Markov chain analysis on a genetic algorithm Proc. 5th Int. Conf. Genetic Algorithms (University of Illinois at Urbana Champaign) pp 146-53
154. Takenaka T, Meng Z Q, Tanaka T and Chew W C 1997 Local shape function combined with genetic algorithm applied to inverse scattering for strips Microw. Opt. Technol. Lett. 16 337-41
155. Theraulaz G and Bonabeau E 1999 A brief history of stigmergy Artif. Life 5 97-116
156. Travassos X L, Vieira D A G, Ida N, Vollaire C and Nicolas A 2008 Inverse algorithms for the GPR assessment of concrete structures IEEE Trans. Magn. 44 994-7
157. Trelea I C 2003 The particle swarm optimization algorithm: convergence analysis and parameter selection Inform. Process. Lett. 85 317-25
158. Vanderplaats G N 1984 Numerical Optimization Techniques for Engineering Design: With Applications (New York: McGraw-Hill)
159. Vose M D and Liepins G E 1991 Punctuated equilibria in genetic search Complex Syst. 5 31-44
160. Wang W, Lu Y, Fu J and Xiong Y Z 2005 Particle swarm optimization and finite-element based approach for microwave filter design IEEE Trans. Magn. 41 1800-3
161. Weile D S and Michielssen E 1997 Genetic algorithm optimization applied to electromagnetics: a review IEEE Trans. Antennas Propag. 45 343-53
162. Weishui W and Chen X 1996 Convergence theorem of genetic algorithm Proc. 1996 IEEE Int. Conf. Systems, Man, and Cybernetics (Beijing, China) pp 1676-81
163. Wildman R A and Weile D S 2007 Geometry reconstruction of conducting cylinders using genetic programming IEEE Trans. Antennas Propag. 55 629-36
164. Wildman R A and Weile D S 2008 Greedy search and a hybrid local optimization/genetic algorithm for tree-based inverse scattering Microw. Opt. Technol. Lett. 50 822-5
165. Wolpert D H and Macready W G 1997 No free lunch theorems for optimization IEEE Trans. Evol. Comput. 1 67-82
166. Xiao F and Yabe H 1998 Microwave imaging of perfectly conducting cylinders from real data by micro genetic algorithm couple with deterministic method IEICE Trans. Electron. E 81-C 1784-92
167. Xu M, Sabouni A, Thulasiraman P, Noghanian S and Pistorius S 2007 Image reconstruction using microwave tomography for breast cancer detection on distributed memory machine Proc. 2007 Int. Conf. Parallel Processing (ICPP 2007) (Xi'an, China, September 10-14, 2007) p 36
168. Xue F, Sanderson A C and Graves R J Multi-objective differential evolution algorithm, convergence analysis, and applications Proc. 2005 IEEE Congress on Evolutionary Computation (Edinburgh, UK, 2-4 September 2005) vol 1 pp 743-50
169. Yang S-Y, Choi H-K and Ra J-W 1997 Reconstruction of a large and high-contrast penetrable object by using the genetic and Levenberg-Marquardt algorithms Microw. Opt. Tech. Lett. 16 17-21
170. Zainud-Deen S H, Hassen W M, Ali E M, Awadalla K H and Sharshar H A 2008 Breast cancer detection using a hybrid finite difference frequency domain and particle swarm optimization techniques Prog. Electromagn. Res. B 3 35-46
171. Zaharie D 2002 Critical values for the control parameters of differential evolution algorithm Proc. 8th Int. Conf. Soft Computing (MENDEL 2002) (Brno, Czech Republic) pp 62-7
172. Zhao B and Li S 2006 A convergence proof for ant colony algorithm Proc. 6th World Congress Intelligent Control and Automation (June 21-23, Dalian, China) vol 1 pp 3072-5
173. Zhou Y and Ling H 2002 Electromagnetic inversion of Ipswich objects with the use of the genetic algorithm Microw. Opt. Technol. Lett. 33 457-9
174. Zhou Y, Li J and Ling H 2003 Shape inversion of metallic cavities using hybrid genetic algorithm combined with tabu list Electron. Lett. 39 280-1
175. Zitzler E, Deb K, Thiele L, Coello C and Corne D 2001 Evolutionary multi-criterion optimization Proc. 1st Int. Conf. (EMO'01) vol 1993 (Berlin: Springer)