Skip to main content
Top
Published in: Soft Computing 7/2021

13-01-2021 | Methodologies and Application

An improved adaptive hybrid firefly differential evolution algorithm for passive target localization

Authors: Maja B. Rosić, Mirjana I. Simić, Predrag V. Pejović

Published in: Soft Computing | Issue 7/2021

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This paper considers a passive target localization problem based on the noisy time of arrival measurements obtained from multiple receivers and a single transmitter. The maximum likelihood (ML) estimator for this localization problem is formulated as a highly nonlinear and non-convex optimization problem, where conventional optimization methods are not suitable for solving such a problem. Consequently, this paper proposes an improved adaptive hybrid firefly differential evolution (AHFADE) algorithm, based on hybridization of firefly algorithm (FA) and differential evolution (DE) algorithm to estimate the unknown position of the target. The proposed AHFADE algorithm dynamically adjusts the control parameters, thus maintaining high population diversity during the evolution process. This paper aims to improve the accuracy of the global optimal solution by incorporating evolutionary operators of the DE in different searching stages of the FA. In this regard, an adaptive parameter is employed to select an appropriate mutation operator for achieving a proper balance between global exploration and local exploitation. In order to efficiently solve the ML estimation problem, this paper proposes the well-known semidefinite programming (SDP) method to convert the non-convex problem into a convex one. The simulation results obtained from the proposed AHFADE algorithm and well-known algorithms, such as SDP, DE and FA, are compared against Cramér–Rao lower bound (CRLB). The statistical analysis has been performed to compare the performance of the proposed AHFADE algorithm with several well-known algorithms on CEC2014 benchmark problems. The obtained simulation results show that the proposed AHFADE algorithm is more robust in high-noise environments compared to existing algorithms.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Appendix
Available only for authorised users
Literature
go back to reference Alweshah M, Abdullah S (2015) Hybridizing firefly algorithms with a probabilistic neural network for solving classification problems. Appl Soft Comput 35:513–524 Alweshah M, Abdullah S (2015) Hybridizing firefly algorithms with a probabilistic neural network for solving classification problems. Appl Soft Comput 35:513–524
go back to reference Arora JS (2004) Introduction to optimum design. Elsevier, Amsterdam Arora JS (2004) Introduction to optimum design. Elsevier, Amsterdam
go back to reference Asmaa L, Hatim KA, Abdelaaziz M (2014) Localization algorithms research in wireless sensor network based on multilateration and trilateration techniques. In: 2014 3rd IEEE international colloquium in information science and technology (CIST), IEEE, pp 415–419 Asmaa L, Hatim KA, Abdelaaziz M (2014) Localization algorithms research in wireless sensor network based on multilateration and trilateration techniques. In: 2014 3rd IEEE international colloquium in information science and technology (CIST), IEEE, pp 415–419
go back to reference Awad NH, Ali MZ, Mallipeddi R, Suganthan PN (2018) An improved differential evolution algorithm using efficient adapted surrogate model for numerical optimization. Inf Sci 451:326–347MathSciNet Awad NH, Ali MZ, Mallipeddi R, Suganthan PN (2018) An improved differential evolution algorithm using efficient adapted surrogate model for numerical optimization. Inf Sci 451:326–347MathSciNet
go back to reference Aydilek IB (2018) A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems. Appl Soft Comput 66:232–249 Aydilek IB (2018) A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems. Appl Soft Comput 66:232–249
go back to reference Baraldi P, Cannarile F, Di Maio F, Zio E (2016) Hierarchical k-nearest neighbours classification and binary differential evolution for fault diagnostics of automotive bearings operating under variable conditions. Eng Appl Artif Intell 56:1–13 Baraldi P, Cannarile F, Di Maio F, Zio E (2016) Hierarchical k-nearest neighbours classification and binary differential evolution for fault diagnostics of automotive bearings operating under variable conditions. Eng Appl Artif Intell 56:1–13
go back to reference Bishop AN, Fidan B, Anderson BD, Doğançay K, Pathirana PN (2010) Optimality analysis of sensor-target localization geometries. Automatica 46(3):479–492MathSciNetMATH Bishop AN, Fidan B, Anderson BD, Doğançay K, Pathirana PN (2010) Optimality analysis of sensor-target localization geometries. Automatica 46(3):479–492MathSciNetMATH
go back to reference Biswas P, Liang TC, Toh KC, Ye Y, Wang TC (2006) Semidefinite programming approaches for sensor network localization with noisy distance measurements. IEEE Trans Autom Sci Eng 3(4):360–371 Biswas P, Liang TC, Toh KC, Ye Y, Wang TC (2006) Semidefinite programming approaches for sensor network localization with noisy distance measurements. IEEE Trans Autom Sci Eng 3(4):360–371
go back to reference Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, CambridgeMATH Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, CambridgeMATH
go back to reference Brest J, Greiner S, Boskovic B, Mernik M, Zumer V (2006) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6):646–657 Brest J, Greiner S, Boskovic B, Mernik M, Zumer V (2006) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6):646–657
go back to reference Cakir O, Kaya I, Yazgan A, Cakir O, Tugcu E (2014) Emitter location finding using particle swarm optimization. Radioengineering 23(1):252–258 Cakir O, Kaya I, Yazgan A, Cakir O, Tugcu E (2014) Emitter location finding using particle swarm optimization. Radioengineering 23(1):252–258
go back to reference Chalise BK, Zhang YD, Amin MG, Himed B (2014) Target localization in a multi-static passive radar system through convex optimization. Signal Process 102:207–215 Chalise BK, Zhang YD, Amin MG, Himed B (2014) Target localization in a multi-static passive radar system through convex optimization. Signal Process 102:207–215
go back to reference Chan FK, So HC, Ma WK, Lui KW (2013) A flexible semi-definite programming approach for source localization problems. Digital Signal Process 23(2):601–609MathSciNet Chan FK, So HC, Ma WK, Lui KW (2013) A flexible semi-definite programming approach for source localization problems. Digital Signal Process 23(2):601–609MathSciNet
go back to reference Choi KH, Ra WS, Park SY, Park JB (2014) Robust least squares approach to passive target localization using ultrasonic receiver array. IEEE Trans Ind Electr 61(4):1993–2002 Choi KH, Ra WS, Park SY, Park JB (2014) Robust least squares approach to passive target localization using ultrasonic receiver array. IEEE Trans Ind Electr 61(4):1993–2002
go back to reference Chowdhury TJ, Elkin C, Devabhaktuni V, Rawat DB, Oluoch J (2016) Advances on localization techniques for wireless sensor networks: A survey. Comput Netw 110:284–305 Chowdhury TJ, Elkin C, Devabhaktuni V, Rawat DB, Oluoch J (2016) Advances on localization techniques for wireless sensor networks: A survey. Comput Netw 110:284–305
go back to reference Cui L, Li G, Lin Q, Chen J, Lu N (2016) Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations. Comput Oper Res 67:155–173MathSciNetMATH Cui L, Li G, Lin Q, Chen J, Lu N (2016) Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations. Comput Oper Res 67:155–173MathSciNetMATH
go back to reference Das S, Mullick SS, Suganthan PN (2016) Recent advances in differential evolution: an updated survey. Swarm Evol Comput 27:1–30 Das S, Mullick SS, Suganthan PN (2016) Recent advances in differential evolution: an updated survey. Swarm Evol Comput 27:1–30
go back to reference Deak G, Curran K, Condell J (2012) A survey of active and passive indoor localisation systems. Comput Commun 35(16):1939–1954 Deak G, Curran K, Condell J (2012) A survey of active and passive indoor localisation systems. Comput Commun 35(16):1939–1954
go back to reference Derrac J, García S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3–18 Derrac J, García S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3–18
go back to reference Destino G, Abreu G (2011) On the maximum likelihood approach for source and network localization. IEEE Trans Signal Process 59(10):4954–4970MathSciNetMATH Destino G, Abreu G (2011) On the maximum likelihood approach for source and network localization. IEEE Trans Signal Process 59(10):4954–4970MathSciNetMATH
go back to reference Einemo M, So HC (2015) Weighted least squares algorithm for target localization in distributed MIMO radar. Signal Process 115:144–150 Einemo M, So HC (2015) Weighted least squares algorithm for target localization in distributed MIMO radar. Signal Process 115:144–150
go back to reference Goel R, Maini R (2018) A hybrid of ant colony and firefly algorithms (hafa) for solving vehicle routing problems. J Comput Sci 25:28–37MathSciNet Goel R, Maini R (2018) A hybrid of ant colony and firefly algorithms (hafa) for solving vehicle routing problems. J Comput Sci 25:28–37MathSciNet
go back to reference Goyal S, Patterh MS (2014) Wireless sensor network localization based on cuckoo search algorithm. Wirel Pers Commun 79(1):223–234 Goyal S, Patterh MS (2014) Wireless sensor network localization based on cuckoo search algorithm. Wirel Pers Commun 79(1):223–234
go back to reference Grant M, Boyd S (2008) Graph implementations for nonsmooth convex programs. In: Blondel V, Boyd S, Kimura H (eds) Recent advances in learning and control, lecture notes in control and information sciences. Springer-Verlag Limited, Berlin, pp 95–110 Grant M, Boyd S (2008) Graph implementations for nonsmooth convex programs. In: Blondel V, Boyd S, Kimura H (eds) Recent advances in learning and control, lecture notes in control and information sciences. Springer-Verlag Limited, Berlin, pp 95–110
go back to reference Guo L, Wang GG, Wang H (2013) Wang D (2013) An effective hybrid firefly algorithm with harmony search for global numerical optimization. Sci World J Guo L, Wang GG, Wang H (2013) Wang D (2013) An effective hybrid firefly algorithm with harmony search for global numerical optimization. Sci World J
go back to reference Huang B, Xie L, Yang Z (2015) TDOA-based source localization with distance-dependent noises. IEEE Trans Wirel Commun 14(1):468–480 Huang B, Xie L, Yang Z (2015) TDOA-based source localization with distance-dependent noises. IEEE Trans Wirel Commun 14(1):468–480
go back to reference Jiang Y, Liu M, Chen T, Gao L (2018) TDOA passive location based on cuckoo search algorithm. J Shanghai Jiaotong Univ (Sci) 23(3):368–375 Jiang Y, Liu M, Chen T, Gao L (2018) TDOA passive location based on cuckoo search algorithm. J Shanghai Jiaotong Univ (Sci) 23(3):368–375
go back to reference Kaur A, Kumar P, Gupta GP (2016) A novel DV-Hop algorithm based on gauss-newton method. In: 2016 4th international conference on parallel. Distributed and grid computing (PDGC), IEEE, pp 625–629 Kaur A, Kumar P, Gupta GP (2016) A novel DV-Hop algorithm based on gauss-newton method. In: 2016 4th international conference on parallel. Distributed and grid computing (PDGC), IEEE, pp 625–629
go back to reference Kocuk B, Dey S, Sun X (2016) Strong SOCP relaxations for the optimal power flow problem. Oper Res 64:1177–1196MathSciNetMATH Kocuk B, Dey S, Sun X (2016) Strong SOCP relaxations for the optimal power flow problem. Oper Res 64:1177–1196MathSciNetMATH
go back to reference Kuila P, Gupta SK, Jana PK (2013) A novel evolutionary approach for load balanced clustering problem for wireless sensor networks. Swarm Evol Comput 12:48–56 Kuila P, Gupta SK, Jana PK (2013) A novel evolutionary approach for load balanced clustering problem for wireless sensor networks. Swarm Evol Comput 12:48–56
go back to reference Kulkarni VR, Desai V, Kulkarni RV (2019) A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks. Wirel Netw 25(5):2789–2803 Kulkarni VR, Desai V, Kulkarni RV (2019) A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks. Wirel Netw 25(5):2789–2803
go back to reference Li Z, Chung PJ, Mulgrew B (2017) Distributed target localization using quantized received signal strength. Signal Process 134:214–223 Li Z, Chung PJ, Mulgrew B (2017) Distributed target localization using quantized received signal strength. Signal Process 134:214–223
go back to reference Liang JJ, Qu BY, Suganthan PN (2013) Problem definitions and evaluation criteria for the cec 2014 special session and competition on single objective real-parameter numerical optimization. Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore, Computational Intelligence Laboratory, p 635 Liang JJ, Qu BY, Suganthan PN (2013) Problem definitions and evaluation criteria for the cec 2014 special session and competition on single objective real-parameter numerical optimization. Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore, Computational Intelligence Laboratory, p 635
go back to reference Lieu QX, Do DTT, Lee J (2018) An adaptive hybrid evolutionary firefly algorithm for shape and size optimization of truss structures with frequency constraints. Comput Struct 195:99–112 Lieu QX, Do DTT, Lee J (2018) An adaptive hybrid evolutionary firefly algorithm for shape and size optimization of truss structures with frequency constraints. Comput Struct 195:99–112
go back to reference Lin L, So HC, Chan FK, Chan YT, Ho K (2013) A new constrained weighted least squares algorithm for TDOA-based localization. Signal Process 93(11):2872–2878 Lin L, So HC, Chan FK, Chan YT, Ho K (2013) A new constrained weighted least squares algorithm for TDOA-based localization. Signal Process 93(11):2872–2878
go back to reference Luthra J, Pal SK (2011) A hybrid firefly algorithm using genetic operators for the cryptanalysis of a monoalphabetic substitution cipher. In: Information and communication technologies (WICT), 2011 world congress on, IEEE, pp 202–206 Luthra J, Pal SK (2011) A hybrid firefly algorithm using genetic operators for the cryptanalysis of a monoalphabetic substitution cipher. In: Information and communication technologies (WICT), 2011 world congress on, IEEE, pp 202–206
go back to reference Mohamed AW (2017) Almazyad AS (2017) Differential evolution with novel mutation and adaptive crossover strategies for solving large scale global optimization problems. Appl Comput Intell Soft Comput Mohamed AW (2017) Almazyad AS (2017) Differential evolution with novel mutation and adaptive crossover strategies for solving large scale global optimization problems. Appl Comput Intell Soft Comput
go back to reference Mohamed AW, Suganthan PN (2018) Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation. Soft Computing 22(10):3215–3235 Mohamed AW, Suganthan PN (2018) Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation. Soft Computing 22(10):3215–3235
go back to reference Noroozi A, Sebt MA (2015) Target localization from bistatic range measurements in multi-transmitter multi-receiver passive radar. IEEE Signal Process Lett 22(12):2445–2449 Noroozi A, Sebt MA (2015) Target localization from bistatic range measurements in multi-transmitter multi-receiver passive radar. IEEE Signal Process Lett 22(12):2445–2449
go back to reference Qian W, Chai J, Xu Z, Zhang Z (2018) Differential evolution algorithm with multiple mutation strategies based on roulette wheel selection. Appl Intell 48:3612–3629 Qian W, Chai J, Xu Z, Zhang Z (2018) Differential evolution algorithm with multiple mutation strategies based on roulette wheel selection. Appl Intell 48:3612–3629
go back to reference Qu X, Xie L (2016) An efficient convex constrained weighted least squares source localization algorithm based on TDOA measurements. Signal Process 119:142–152 Qu X, Xie L (2016) An efficient convex constrained weighted least squares source localization algorithm based on TDOA measurements. Signal Process 119:142–152
go back to reference Rao SS, Rao SS (2009) Engineering optimization: theory and practice. John Wiley & Sons, New Jersey Rao SS, Rao SS (2009) Engineering optimization: theory and practice. John Wiley & Sons, New Jersey
go back to reference Sachs J (2013) Handbook of ultra-wideband short-range sensing: theory sensors, applications. John Wiley & Sons, New JerseyMATH Sachs J (2013) Handbook of ultra-wideband short-range sensing: theory sensors, applications. John Wiley & Sons, New JerseyMATH
go back to reference Sadowski S, Spachos P (2018) RSSI-based indoor localization with the internet of things. IEEE Access 6:30149–30161 Sadowski S, Spachos P (2018) RSSI-based indoor localization with the internet of things. IEEE Access 6:30149–30161
go back to reference Shen J, Molisch AF, Salmi J (2012) Accurate passive location estimation using TOA measurements. IEEE Trans Wirel Commun 11(6):2182–2192 Shen J, Molisch AF, Salmi J (2012) Accurate passive location estimation using TOA measurements. IEEE Trans Wirel Commun 11(6):2182–2192
go back to reference Singh SP, Sharma S (2015) Range free localization techniques in wireless sensor networks: a review. Proc Comput Sci 57:7–16 Singh SP, Sharma S (2015) Range free localization techniques in wireless sensor networks: a review. Proc Comput Sci 57:7–16
go back to reference Storn R, Price K (1997) Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341–359MathSciNetMATH Storn R, Price K (1997) Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341–359MathSciNetMATH
go back to reference Tanabe R, Fukunaga A (2013) (2013) Success-history based parameter adaptation for differential evolution. Evolutionary computation (CEC). IEEE congress on, IEEE, pp 71–78 Tanabe R, Fukunaga A (2013) (2013) Success-history based parameter adaptation for differential evolution. Evolutionary computation (CEC). IEEE congress on, IEEE, pp 71–78
go back to reference Wang G, Li Y, Ansari N (2013) A semidefinite relaxation method for source localization using TDOA and FDOA measurements. IEEE Trans Veh Technol 62(2):853–862 Wang G, Li Y, Ansari N (2013) A semidefinite relaxation method for source localization using TDOA and FDOA measurements. IEEE Trans Veh Technol 62(2):853–862
go back to reference Wang H, Cui Z, Sun H, Rahnamayan S, Yang XS (2017) Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism. Soft Comput 21(18):5325–5339 Wang H, Cui Z, Sun H, Rahnamayan S, Yang XS (2017) Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism. Soft Comput 21(18):5325–5339
go back to reference Wang Y (2015) Linear least squares localization in sensor networks. EURASIP J Wirel Commun Netw 2015(1):51 Wang Y (2015) Linear least squares localization in sensor networks. EURASIP J Wirel Commun Netw 2015(1):51
go back to reference Wang Y, Wu Y (2016) An efficient semidefinite relaxation algorithm for moving source localization using TDOA and FDOA measurements. IEEE Commun Lett 21(1):80–83 Wang Y, Wu Y (2016) An efficient semidefinite relaxation algorithm for moving source localization using TDOA and FDOA measurements. IEEE Commun Lett 21(1):80–83
go back to reference Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evol Comput 15(1):55–66 Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evol Comput 15(1):55–66
go back to reference Wang Y, Ma S, Chen CP (2014) TOA-based passive localization in quasi-synchronous networks. IEEE Commun Lett 18(4):592–595 Wang Y, Ma S, Chen CP (2014) TOA-based passive localization in quasi-synchronous networks. IEEE Commun Lett 18(4):592–595
go back to reference Wu G, Shen X, Li H, Chen H, Lin A, Suganthan PN (2018) Ensemble of differential evolution variants. Inf Sci 423:172–186MathSciNet Wu G, Shen X, Li H, Chen H, Lin A, Suganthan PN (2018) Ensemble of differential evolution variants. Inf Sci 423:172–186MathSciNet
go back to reference Wu N, Yuan W, Wang H, Kuang J (2016) TOA-based passive localization of multiple targets with inaccurate receivers based on belief propagation on factor graph. Digital Signal Process 49:14–23 Wu N, Yuan W, Wang H, Kuang J (2016) TOA-based passive localization of multiple targets with inaccurate receivers based on belief propagation on factor graph. Digital Signal Process 49:14–23
go back to reference Wu P, Su S, Zuo Z, Guo X, Sun B, Wen X (2019) Time difference of arrival (TDoA) localization combining weighted least squares and firefly algorithm. Sensors 19(11):2554 Wu P, Su S, Zuo Z, Guo X, Sun B, Wen X (2019) Time difference of arrival (TDoA) localization combining weighted least squares and firefly algorithm. Sensors 19(11):2554
go back to reference Xu S, Doğançay K (2015) Optimal sensor deployment for 3D AOA target localization. In: 2015 IEEE international conference on acoustics. Speech and signal processing (ICASSP), IEEE, pp 2544–2548 Xu S, Doğançay K (2015) Optimal sensor deployment for 3D AOA target localization. In: 2015 IEEE international conference on acoustics. Speech and signal processing (ICASSP), IEEE, pp 2544–2548
go back to reference Yan J, Zhang X, Luo X, Wang Y, Chen C, Guan X (2018) Asynchronous localization with mobility prediction for underwater acoustic sensor networks. IEEE Trans Veh Technol 67(3):2543–2556 Yan J, Zhang X, Luo X, Wang Y, Chen C, Guan X (2018) Asynchronous localization with mobility prediction for underwater acoustic sensor networks. IEEE Trans Veh Technol 67(3):2543–2556
go back to reference Yang XS (2009) Firefly algorithms for multimodal optimization. In: International symposium on stochastic algorithms, Springer, pp 169–178 Yang XS (2009) Firefly algorithms for multimodal optimization. In: International symposium on stochastic algorithms, Springer, pp 169–178
go back to reference Yang XS (2010a) Firefly algorithm, levy flights and global optimization. In: Research and development in intelligent systems 26, Springer, pp 209–218 Yang XS (2010a) Firefly algorithm, levy flights and global optimization. In: Research and development in intelligent systems 26, Springer, pp 209–218
go back to reference Yang XS (2010b) Firefly algorithm, stochastic test functions and design optimisation. Int J Bio-Inspired Comput 2(2):78–84 Yang XS (2010b) Firefly algorithm, stochastic test functions and design optimisation. Int J Bio-Inspired Comput 2(2):78–84
go back to reference Zekavat R, Buehrer RM (2011) Handbook of position location: theory, practice and advances, vol 27. John Wiley & Sons, New Jersey Zekavat R, Buehrer RM (2011) Handbook of position location: theory, practice and advances, vol 27. John Wiley & Sons, New Jersey
go back to reference Zhang D, Fang Z, Wang Y, Sun H (2015a) Research on an improved DV-Hop localization algorithm based on PSODE in WSN. J Commun 10(9): Zhang D, Fang Z, Wang Y, Sun H (2015a) Research on an improved DV-Hop localization algorithm based on PSODE in WSN. J Commun 10(9):
go back to reference Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5):945–958 Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5):945–958
go back to reference Zhang L, Liu L, Yang XS, Dai Y (2016) A novel hybrid firefly algorithm for global optimization. PloS ONE 11(9):e0163230 Zhang L, Liu L, Yang XS, Dai Y (2016) A novel hybrid firefly algorithm for global optimization. PloS ONE 11(9):e0163230
go back to reference Zhang Y, Wei D, Fu W, Yang B (2014) Target positioning with GDOP assisted nodes selection algorithm in wireless sensor networks. Int J Distrib Sensor Netw 10(6):404812 Zhang Y, Wei D, Fu W, Yang B (2014) Target positioning with GDOP assisted nodes selection algorithm in wireless sensor networks. Int J Distrib Sensor Netw 10(6):404812
go back to reference Zhang Y, Wang S, Ji G (2015b) A comprehensive survey on particle swarm optimization algorithm and its applications. Math Probl Eng Zhang Y, Wang S, Ji G (2015b) A comprehensive survey on particle swarm optimization algorithm and its applications. Math Probl Eng
Metadata
Title
An improved adaptive hybrid firefly differential evolution algorithm for passive target localization
Authors
Maja B. Rosić
Mirjana I. Simić
Predrag V. Pejović
Publication date
13-01-2021
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 7/2021
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-020-05554-8

Other articles of this Issue 7/2021

Soft Computing 7/2021 Go to the issue

Premium Partner