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18-04-2018 | Methodologies and Application

PSO-based improved multi-flocks migrating birds optimization (IMFMBO) algorithm for solution of discrete problems

Authors: Vahit Tongur, Erkan Ülker

Published in: Soft Computing | Issue 14/2019

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Abstract

In this paper, we proposed an improved migrating birds optimization algorithm to solve discrete problem. It is a metaheuristic search algorithm that is inspired by V formation during the migration of migratory birds. Proposed algorithm has two main modifications on basic migrating birds algorithm. Firstly, multi-flocks are used instead of single flock in order to avoid local minimum. Secondly, these flocks interact with each other for the more detailed search around flock that has got better solutions. This interaction is inspired by particle swarm optimization algorithm. Also, insertion method is used for neighborhood in migrating birds optimization algorithm. As a discrete problem, traveling salesman problem is chosen. Performance of the proposed algorithm is tested on some of symmetric benchmark problems from TSPLIB. Obtained results show that proposed method is superior to basic migrating birds algorithm.

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Azadeh A, Farahani MH, Eivazy H, Nazari-Shirkouhi S, Asadipour G (2013) A hybrid meta-heuristic algorithm for optimization of crew scheduling. Appl Soft Comput 13(1):158–164CrossRefMATH

BañOs R, Ortega J, Gil C, MáRquez AL, De Toro F (2013) A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows. Comput Ind Eng 65(2):286–296CrossRef

Debels D, De Reyck B, Leus R, Vanhoucke M (2006) A hybrid scatter search/electromagnetism meta-heuristic for project scheduling. Eur J Oper Res 169(2):638–653MathSciNetCrossRefMATH

Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39CrossRef

Duan H, Yu Y, Zhang X, Shao S (2010) Three-dimension path planning for ucav using hybrid meta-heuristic aco-de algorithm. Simul Model Pract Theory 18(8):1104–1115CrossRef

Duman E, Elikucuk I (2013) Solving credit card fraud detection problem by the new metaheuristics migrating birds optimization. In: International work-conference on artificial neural networks. Springer, pp 62–71

Duman E, Uysal M, Alkaya AF (2012) Migrating birds optimization: a new metaheuristic approach and its performance on quadratic assignment problem. Inf Sci 217:65–77MathSciNetCrossRef

Dutta M et al (2015) TSP solution using dimensional ant colony optimization. In: 2015 Fifth international conference on advanced computing & communication technologies (ACCT). IEEE, pp 506–512

Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, 1995. MHS’95. IEEE, pp 39–43

Gao KZ, Suganthan PN, Chua TJ (2013) An enhanced migrating birds optimization algorithm for no-wait flow shop scheduling problem. In: 2013 ieee symposium on computational intelligence in scheduling (SCIS). IEEE, pp 9–13

Geng X, Chen Z, Yang W, Shi D, Zhao K (2011) Solving the traveling salesman problem based on an adaptive simulated annealing algorithm with greedy search. Appl Soft Comput 11(4):3680–3689CrossRef

Gülcü Ş, Mahi M, Baykan Ö.K, Kodaz H (2016) A parallel cooperative hybrid method based on ant colony optimization and 3-opt algorithm for solving traveling salesman problem. Soft Comput 1–17

Helsgaun K (2000) An effective implementation of the Lin–Kernighan traveling salesman heuristic. Eur J Oper Res 126(1):106–130 Kindly provide volume number for the references Gulcu et al. (2016) and Lv et al. (2017)MathSciNetCrossRefMATH

Huang L, Wang Gc, Bai T, Wang Z (2017) An improved fruit fly optimization algorithm for solving traveling salesman problem. Front Inf Technol Electron Eng 18(10):1525–1533CrossRef

Jolai F, Rabiee M, Asefi H (2012) A novel hybrid meta-heuristic algorithm for a no-wait flexible flow shop scheduling problem with sequence dependent setup times. Int J Prod Res 50(24):7447–7466CrossRef

Karapetyan D, Gutin G (2011) Lin–Kernighan heuristic adaptations for the generalized traveling salesman problem. Eur J Oper Res 208(3):221–232MathSciNetCrossRefMATH

Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. In: 1997 IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, 1997. IEEE, vol. 5, pp 4104–4108

Kıran MS, İşcan H, Gündüz M (2013) The analysis of discrete artificial bee colony algorithm with neighborhood operator on traveling salesman problem. Neural Comput Appl 23(1):9–21CrossRef

Liao CJ, Tseng CT, Luarn P (2007) A discrete version of particle swarm optimization for flowshop scheduling problems. Comput Oper Res 34(10):3099–3111CrossRefMATH

Liu F, Zeng G (2009) Study of genetic algorithm with reinforcement learning to solve the TSP. Expert Syst Appl 36(3):6995–7001MathSciNetCrossRef

Lv SX, Zeng YR, Wang L (2017) An effective fruit fly optimization algorithm with hybrid information exchange and its applications. Int J Mach Learn Cybern 1–26

Ma J, Yang T, Hou ZG, Tan M, Liu D (2008) Neurodynamic programming: a case study of the traveling salesman problem. Neural Comput Appl 17(4):347–355CrossRef

Marinakis Y, Marinaki M, Migdalas A (2016) A hybrid discrete artificial bee colony algorithm for the multicast routing problem. In: European conference on the applications of evolutionary computation. Springer, pp 203–218

Meer K (2007) Simulated annealing versus metropolis for a TSP instance. Inf Process Lett 104(6):216–219MathSciNetCrossRefMATH

Niroomand S, Hadi-Vencheh A, Şahin R, Vizvári B (2015) Modified migrating birds optimization algorithm for closed loop layout with exact distances in flexible manufacturing systems. Expert Syst Appl 42(19):6586–6597CrossRef

Pan QK, Dong Y (2014) An improved migrating birds optimisation for a hybrid flowshop scheduling with total flowtime minimisation. Inf Sci 277:643–655MathSciNetCrossRefMATH

Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1(1):33–57CrossRef

Poorzahedy H, Rouhani OM (2007) Hybrid meta-heuristic algorithms for solving network design problem. Eur J Oper Res 182(2):578–596MathSciNetCrossRefMATH

Rao ARM, Shyju P (2008) Development of a hybrid meta-heuristic algorithm for combinatorial optimisation and its application for optimal design of laminated composite cylindrical skirt. Comput Struct 86(7):796–815CrossRef

Reinelt G (1991) Tspliba traveling salesman problem library. ORSA J Comput 3(4):376–384CrossRefMATH

Salcedo-Sanz S, Xu Y, Yao X (2006) Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems. Comput Oper Res 33(3):820–835CrossRefMATH

Shi XH, Liang YC, Lee HP, Lu C, Wang Q (2007) Particle swarm optimization-based algorithms for TSP and generalized TSP. Inf Process Lett 103(5):169–176MathSciNetCrossRefMATH

Tasgetiren MF, Sevkli M, Liang YC, Gencyilmaz G (2004a) Particle swarm optimization algorithm for permutation flowshop sequencing problem. In: International workshop on ant colony optimization and swarm intelligence. Springer, pp 382–389

Tasgetiren MF, Sevkli M, Liang YC, Gencyilmaz G (2004b) Particle swarm optimization algorithm for single machine total weighted tardiness problem. In: Congress on evolutionary computation, 2004, CEC2004. IEEE, vol. 2, pp 1412–1419

Tongur V, Ülker E (2014) Migrating birds optimization for flow shop sequencing problem. J Comput Commun 2(04):142CrossRef

Tongur V, Ülker E (2016) The analysis of migrating birds optimization algorithm with neighborhood operator on traveling salesman problem. In: Intelligent and evolutionary systems. Springer, pp 227–237

Tuba M, Jovanovic R (2013) Improved ACO algorithm with pheromone correction strategy for the traveling salesman problem. Int J Comput Commun Control 8(3):477–485CrossRef

Wang X, Xu G (2011) Hybrid differential evolution algorithm for traveling salesman problem. Procedia Eng 15:2716–2720CrossRef

Wang KP, Huang L, Zhou CG, Pang W (2003) Particle swarm optimization for traveling salesman problem. In: 2003 International conference on machine learning and cybernetics. IEEE, vol. 3, pp 1583–1585

Wang Z, Geng X, Shao Z (2009) An effective simulated annealing algorithm for solving the traveling salesman problem. J Comput Theor Nanosci 6(7):1680–1686CrossRef

Wang L, Zeng Y, Chen T (2015) Back propagation neural network with adaptive differential evolution algorithm for time series forecasting. Expert Syst Appl 42(2):855–863CrossRef

Wang L, Liu R, Liu S (2016) An effective and efficient fruit fly optimization algorithm with level probability policy and its applications. Knowl-Based Syst 97:158–174CrossRef

Zeng YR, Peng L, Zhang J, Wang L (2016) An effective hybrid differential evolution algorithm incorporating simulated annealing for joint replenishment and delivery problem with trade credit. Int J Comput Intell Syst 9(6):1001–1015CrossRef

Zhong WH, Zhang J, Chen WN (2007) A novel discrete particle swarm optimization to solve traveling salesman problem. In: IEEE congress on evolutionary computation, 2007, CEC 2007. IEEE, pp 3283–3287

Zhong Y, Wu C, Li L, Ning Z (2008) The study of neighborhood structure of tabu search algorithm for traveling salesman problem. In: Fourth international conference on natural computation, 2008, ICNC’08. IEEE, vol. 1, pp 491–495

Zhou Y, Luo Q, Chen H, He A, Wu J (2015) A discrete invasive weed optimization algorithm for solving traveling salesman problem. Neurocomputing 151:1227–1236CrossRef

Title: PSO-based improved multi-flocks migrating birds optimization (IMFMBO) algorithm for solution of discrete problems
Authors: Vahit Tongur
Erkan Ülker
Publication date: 18-04-2018
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 14/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3199-5

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