A hybrid Particle Swarm Optimization – Variable Neighborhood Search algorithm for Constrained Shortest Path problems
•The Constrained Shortest Path problem is solved using a hybridized version of PSO.•A different equation for the particles’ velocities is used.•A novel expanding neighborhood topology is applied.•A VNS algorithm is applied in order to optimize the particles’ position.•The algorithm is tested in a nu...
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| Vydané v: | European journal of operational research Ročník 261; číslo 3; s. 819 - 834 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
16.09.2017
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| ISSN: | 0377-2217, 1872-6860, 1872-6860 |
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| Abstract | •The Constrained Shortest Path problem is solved using a hybridized version of PSO.•A different equation for the particles’ velocities is used.•A novel expanding neighborhood topology is applied.•A VNS algorithm is applied in order to optimize the particles’ position.•The algorithm is tested in a number of modified instances from the TSPLIB.
In this paper, a well known NP-hard problem, the Constrained Shortest Path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based swarm intelligence algorithm that simulates the social behavior of social organisms by using the physical movements of the particles in the swarm. A Variable Neighborhood Search (VNS) algorithm is applied in order to optimize the particles’ position. In the proposed algorithm, the Particle Swarm Optimization with combined Local and Global Expanding Neighborhood Topology (PSOLGENT), a different equation for the velocities of particles is given and a novel expanding neighborhood topology is used. Another issue in the application of the VNS algorithm in the Constrained Shortest Path problem is which local search algorithms are suitable from this problem. In this paper, a number of continuous local search algorithms are used. The algorithm is tested in a number of modified instances from the TSPLIB and comparisons with classic versions of PSO and with other versions of the proposed method are performed. Also, the results of the algorithm are compared with the results of a number of metaheuristic and evolutionary algorithms. The results obtained are very satisfactory and strengthen the efficiency of the algorithm. |
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| AbstractList | •The Constrained Shortest Path problem is solved using a hybridized version of PSO.•A different equation for the particles’ velocities is used.•A novel expanding neighborhood topology is applied.•A VNS algorithm is applied in order to optimize the particles’ position.•The algorithm is tested in a number of modified instances from the TSPLIB.
In this paper, a well known NP-hard problem, the Constrained Shortest Path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based swarm intelligence algorithm that simulates the social behavior of social organisms by using the physical movements of the particles in the swarm. A Variable Neighborhood Search (VNS) algorithm is applied in order to optimize the particles’ position. In the proposed algorithm, the Particle Swarm Optimization with combined Local and Global Expanding Neighborhood Topology (PSOLGENT), a different equation for the velocities of particles is given and a novel expanding neighborhood topology is used. Another issue in the application of the VNS algorithm in the Constrained Shortest Path problem is which local search algorithms are suitable from this problem. In this paper, a number of continuous local search algorithms are used. The algorithm is tested in a number of modified instances from the TSPLIB and comparisons with classic versions of PSO and with other versions of the proposed method are performed. Also, the results of the algorithm are compared with the results of a number of metaheuristic and evolutionary algorithms. The results obtained are very satisfactory and strengthen the efficiency of the algorithm. In this paper, a well known NP-hard problem, the constrained shortest path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based swarm intelligence algorithm that simulates the social behavior of social organisms by using the physical movements of the particles in the swarm. A Variable Neighborhood Search (VNS) algorithm is applied in order to optimize the particles’ position. In the proposed algorithm, the Particle Swarm Optimization with combined Local and Global Expanding Neighborhood Topology (PSOLGENT), a different equation for the velocities of particles is given and a novel expanding neighborhood topology is used. Another issue in the application of the VNS algorithm in the Constrained Shortest Path problem is which local search algorithms are suitable from this problem. In this paper, a number of continuous local search algorithms are used. The algorithm is tested in a number of modified instances from the TSPLIB and comparisons with classic versions of PSO and with other versions of the proposed method are performed. Also, the results of the algorithm are compared with the results of a number of metaheuristic and evolutionary algorithms. The results obtained are very satisfactory and strengthen the efficiency of the algorithm. |
| Author | Migdalas, Athanasios Marinakis, Yannis Sifaleras, Angelo |
| Author_xml | – sequence: 1 givenname: Yannis surname: Marinakis fullname: Marinakis, Yannis email: marinakis@ergasya.tuc.gr organization: School of Production Engineering and Management, Decision Support Systems Laboratory, Technical University of Crete, University Campus, Chania 73100, Greece – sequence: 2 givenname: Athanasios surname: Migdalas fullname: Migdalas, Athanasios email: samig@civil.auth.gr, athmig@ltu.se organization: Department of Civil Engineering, Aristotle University of Thessalonike, 54124 Thessaloniki, Greece – sequence: 3 givenname: Angelo surname: Sifaleras fullname: Sifaleras, Angelo email: sifalera@uom.gr organization: School of Information Sciences, Department of Applied Informatics, University of Macedonia, 156 Egnatias Str., Thessaloniki 54006, Greece |
| BackLink | https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-62564$$DView record from Swedish Publication Index |
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| Cites_doi | 10.1016/j.asoc.2008.01.002 10.1016/j.eswa.2012.12.066 10.1016/S0377-2217(02)00262-X 10.1007/s11047-007-9050-z 10.1016/j.omega.2012.02.002 10.1016/j.eswa.2009.06.085 10.1016/j.cor.2012.07.008 10.1109/TCSI.2006.869907 10.2298/YJOR121120001S 10.1126/science.220.4598.671 10.1007/BF01096763 10.1016/j.swevo.2014.06.001 10.1109/ICEC.1998.699146 10.1016/j.ins.2010.10.015 10.1007/s11047-007-9049-5 10.1109/ICNN.1995.488968 10.1287/ijoc.1.3.190 10.1016/j.engfailanal.2011.02.008 10.1016/j.engappai.2010.02.002 10.1016/0022-247X(66)90020-5 10.1287/ijoc.2.1.4 10.1016/S0377-2217(00)00100-4 10.1109/TEVC.2009.2026270 10.1016/j.engappai.2013.09.011 10.1016/j.asoc.2014.08.013 10.1016/j.amc.2006.12.066 10.1007/s00500-013-0992-z 10.1016/j.asoc.2011.02.032 10.1109/TSMCB.2005.850530 10.1007/s10732-009-9109-3 10.1007/s10479-009-0657-6 10.1016/j.asoc.2012.03.063 10.1109/4235.985692 10.1016/j.knosys.2013.01.011 10.1109/TEVC.2005.857610 10.1007/s11721-007-0002-0 10.1016/j.ins.2012.04.028 10.1016/j.amc.2006.07.026 10.1007/s11047-009-9137-9 10.1016/j.cnsns.2013.03.011 10.1016/j.ins.2012.10.012 10.1007/s10852-007-9073-6 10.1007/BF01386390 10.1016/j.eswa.2013.07.054 10.1002/net.3230190402 10.1023/A:1016568309421 10.1002/net.20247 10.1016/j.trb.2006.12.001 10.1109/CEC.2002.1004493 10.1016/j.cor.2009.03.004 10.5711/morj.14.3.31 10.1002/net.3230100403 10.1109/TEVC.2004.826074 |
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| Keywords | Expanding neighborhood topology Variable Neighborhood Search Particle Swarm Optimization Constrained Shortest Path problem |
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| References | Mohemmed, Sahoo, Geok (bib0051) 2008; 8 Marinakis, Marinaki, Dounias (bib0048) 2010; 23 Zhang, Zhang, Hu, Deng, Mahadevan (bib0071) 2013; 40 Banks, Vincent, Anyakoha (bib0002) 2007; 6 Consoli, Moreno-Perez, Darby-Dowman, Mladenovic (bib0012) 2008 Wang, Lu, Zhang, Wang, Yong Deng (bib0068) 2014; 2014 Shi, Eberhart (bib0062) 1998; 7832 Bonyadi, Li, Michalewicz (bib0006) 2014; 18 Formaneck, Cozzarin (bib0019) 2012; 41 Jiang, Wang, Wang (bib0030) 2013; 18 Cai, Zhang, Zhou, Cao, Tang (bib0008) 2012; 12 Clerc (bib0010) 2006 Dijkstra (bib0014) 1959; 1 Nasir, Das, Maity, Sengupta, Halder, Suganthan (bib0053) 2012; 209 Carlyle, Royset, Wood (bib0009) 2008; 52 Goldberg (bib0024) 1989 Hansen, Mladenović, Moreno-Pérez (bib0027) 2010; 175 Eberhart, Shi (bib0016) 2001 Liang, Qin, Suganthan, Baskarr (bib0038) 2006; 10 Brits, Engelbrecht, Van Den Bergh (bib0007) 2007; 189 Lim, Isa (bib0040) 2014; 27 Glover (bib0022) 1990; 2 Marinakis, Marinaki (bib0044) 2010; 37 Royset, Carlyle, Wood (bib0059) 2009; 14 Beasley, Christofides (bib0004) 1989; 19 Blum, Puchinger, Raidl, Roli (bib0005) 2011; 11 Liu, Zheng, Cai (bib0041) 2013; 44 Kennedy, J., & Mendes, R. (2002). Population structure and particle swarm performance. Proceedings of the 2002 IEEE congress on evolutionary computation, (pp. 1671–1676). Marinakis, Marinaki (bib0043) 2008; 7 Sura, Mahadevan (bib0065) 2011; 18 Feo, Resende (bib0018) 1995; 6 Maruta, Kim, Song, Sugie (bib0049) 2013; 40 Clerc, Kennedy (bib0011) 2002; 6 Dorigo, Stutzle (bib0015) 2004 Ghosh, Das, Kundu, Suresh, Abraham (bib0020) 2012; 182 Niu, Zhu, He, Wu (bib0054) 2007; 185 Marinakis, Marinaki (bib0045) 2010; 37 Marinakis, Marinaki (bib0046) 2013; 7832 Hu, Eberhart (bib0028) 2002 Banks, Vincent, Anyakoha (bib0003) 2008; 7 Glover (bib0021) 1989; 1 Handler, Zang (bib0025) 1980; 10 Consoli, Moreno-Perez, Darby-Dowman, Mladenovic (bib0013) 2010; 9 Sifaleras (bib0063) 2013; 23 Engelbrecht (bib0017) 2007 Parsopoulos, Vrahatis (bib0055) 2002; 1 Joksch (bib0031) 1966; 14 Mohemmed, Sahoo, Geok (bib0052) 2010; 16 Wang, Sun, Li, Rahnamayan, Pan (bib0069) 2013; 223 Tillett, Rao, Sahin, Rao (bib0066) 2005 Lozano, Medaglia (bib0042) 2013; 40 Avella, Boccia, Sforza (bib0001) 2002; 142 Li (bib0037) 2010; 14 Shi, Y., & Eberhart, R. C. (1998a). A modified particle swarm optimizer. Proceedings of the 1998 IEEE World Congress on Computational Intelligence, (pp. 69–73). Lefebvre, Puget, Vilim (bib0036) 2011; 2011 Mendes, Kennedy, Neves (bib0050) 2004; 8 Janson, Middendorf (bib0029) 2005; 35 Tran, Wu, Wang (bib0067) 2013 Kennedy, Eberhart (bib0033) 1995; 4 Hansen, Mladenović (bib0026) 2001; 130 Lim, Isa (bib0039) 2014; 24 Glover, Laguna, Marti (bib0023) 2003 Santos, Coutinho-Rodrigues, Current (bib0060) 2007; 41 Suganthan (bib0064) 1999 Price, Storn, Lampinen (bib0058) 2005 Xiao, Thulasiraman, Xue (bib0070) 2006; 53 Kennedy (bib0032) 1999 Peram, Veeramachaneni, Mohan (bib0056) 2003 Kirkpatrick, Gelatt, Vecchi (bib0035) 1982; 220 Poli, Kennedy, Blackwell (bib0057) 2007; 1 Marinakis, Marinaki (bib0047) 2013; 17 Jiang (10.1016/j.ejor.2017.03.031_bib0030) 2013; 18 Lim (10.1016/j.ejor.2017.03.031_bib0040) 2014; 27 Clerc (10.1016/j.ejor.2017.03.031_sbref0010) 2006 Clerc (10.1016/j.ejor.2017.03.031_bib0011) 2002; 6 Hansen (10.1016/j.ejor.2017.03.031_bib0027) 2010; 175 Banks (10.1016/j.ejor.2017.03.031_bib0002) 2007; 6 Marinakis (10.1016/j.ejor.2017.03.031_bib0046) 2013; 7832 Lozano (10.1016/j.ejor.2017.03.031_bib0042) 2013; 40 Mohemmed (10.1016/j.ejor.2017.03.031_bib0052) 2010; 16 Glover (10.1016/j.ejor.2017.03.031_bib0022) 1990; 2 Feo (10.1016/j.ejor.2017.03.031_bib0018) 1995; 6 Price (10.1016/j.ejor.2017.03.031_bib0058) 2005 Kirkpatrick (10.1016/j.ejor.2017.03.031_bib0035) 1982; 220 Brits (10.1016/j.ejor.2017.03.031_bib0007) 2007; 189 Dorigo (10.1016/j.ejor.2017.03.031_bib0015) 2004 Hu (10.1016/j.ejor.2017.03.031_bib0028) 2002 Tillett (10.1016/j.ejor.2017.03.031_bib0066) 2005 Suganthan (10.1016/j.ejor.2017.03.031_bib0064) 1999 Consoli (10.1016/j.ejor.2017.03.031_bib0012) 2008 Hansen (10.1016/j.ejor.2017.03.031_bib0026) 2001; 130 Janson (10.1016/j.ejor.2017.03.031_bib0029) 2005; 35 Marinakis (10.1016/j.ejor.2017.03.031_bib0045) 2010; 37 Consoli (10.1016/j.ejor.2017.03.031_bib0013) 2010; 9 Mohemmed (10.1016/j.ejor.2017.03.031_bib0051) 2008; 8 Goldberg (10.1016/j.ejor.2017.03.031_bib0024) 1989 Zhang (10.1016/j.ejor.2017.03.031_bib0071) 2013; 40 Poli (10.1016/j.ejor.2017.03.031_bib0057) 2007; 1 Banks (10.1016/j.ejor.2017.03.031_bib0003) 2008; 7 Ghosh (10.1016/j.ejor.2017.03.031_bib0020) 2012; 182 Parsopoulos (10.1016/j.ejor.2017.03.031_bib0055) 2002; 1 Cai (10.1016/j.ejor.2017.03.031_bib0008) 2012; 12 Glover (10.1016/j.ejor.2017.03.031_bib0021) 1989; 1 10.1016/j.ejor.2017.03.031_bib0061 Carlyle (10.1016/j.ejor.2017.03.031_bib0009) 2008; 52 Blum (10.1016/j.ejor.2017.03.031_bib0005) 2011; 11 Nasir (10.1016/j.ejor.2017.03.031_bib0053) 2012; 209 Engelbrecht (10.1016/j.ejor.2017.03.031_bib0017) 2007 Sura (10.1016/j.ejor.2017.03.031_bib0065) 2011; 18 Dijkstra (10.1016/j.ejor.2017.03.031_bib0014) 1959; 1 Formaneck (10.1016/j.ejor.2017.03.031_bib0019) 2012; 41 Niu (10.1016/j.ejor.2017.03.031_bib0054) 2007; 185 Maruta (10.1016/j.ejor.2017.03.031_bib0049) 2013; 40 Glover (10.1016/j.ejor.2017.03.031_bib0023) 2003 Avella (10.1016/j.ejor.2017.03.031_bib0001) 2002; 142 Kennedy (10.1016/j.ejor.2017.03.031_bib0033) 1995; 4 Royset (10.1016/j.ejor.2017.03.031_bib0059) 2009; 14 Mendes (10.1016/j.ejor.2017.03.031_bib0050) 2004; 8 Lefebvre (10.1016/j.ejor.2017.03.031_bib0036) 2011; 2011 Xiao (10.1016/j.ejor.2017.03.031_bib0070) 2006; 53 Handler (10.1016/j.ejor.2017.03.031_bib0025) 1980; 10 Liang (10.1016/j.ejor.2017.03.031_bib0038) 2006; 10 Liu (10.1016/j.ejor.2017.03.031_bib0041) 2013; 44 Sifaleras (10.1016/j.ejor.2017.03.031_bib0063) 2013; 23 Beasley (10.1016/j.ejor.2017.03.031_bib0004) 1989; 19 Bonyadi (10.1016/j.ejor.2017.03.031_bib0006) 2014; 18 Wang (10.1016/j.ejor.2017.03.031_sbref0066) 2014; 2014 Marinakis (10.1016/j.ejor.2017.03.031_bib0043) 2008; 7 Peram (10.1016/j.ejor.2017.03.031_bib0056) 2003 10.1016/j.ejor.2017.03.031_bib0034 Marinakis (10.1016/j.ejor.2017.03.031_bib0047) 2013; 17 Shi (10.1016/j.ejor.2017.03.031_bib0062) 1998; 7832 Wang (10.1016/j.ejor.2017.03.031_bib0069) 2013; 223 Kennedy (10.1016/j.ejor.2017.03.031_bib0032) 1999 Li (10.1016/j.ejor.2017.03.031_bib0037) 2010; 14 Lim (10.1016/j.ejor.2017.03.031_bib0039) 2014; 24 Joksch (10.1016/j.ejor.2017.03.031_bib0031) 1966; 14 Marinakis (10.1016/j.ejor.2017.03.031_bib0044) 2010; 37 Tran (10.1016/j.ejor.2017.03.031_bib0067) 2013 Santos (10.1016/j.ejor.2017.03.031_bib0060) 2007; 41 Eberhart (10.1016/j.ejor.2017.03.031_bib0016) 2001 Marinakis (10.1016/j.ejor.2017.03.031_bib0048) 2010; 23 |
| References_xml | – start-page: 1391 year: 1999 end-page: 1938 ident: bib0032 article-title: Small worlds and mega-minds: Effects of neighborhood topology on particle swarm performance publication-title: Proceedings of IEEE Congress on Evolutionary Computation – volume: 11 start-page: 4135 year: 2011 end-page: 4151 ident: bib0005 article-title: Hybrid metaheuristics in combinatorial optimization: A survey publication-title: Applied Soft Computing – volume: 4 start-page: 1942 year: 1995 end-page: 1948 ident: bib0033 article-title: Particle swarm optimization publication-title: Proceedings of the IEEE International Conference on Neural Networks – volume: 52 start-page: 256 year: 2008 end-page: 270 ident: bib0009 article-title: Lagrangian relaxation and enumeration for solving constrained shortest-path problems publication-title: Networks – volume: 1 start-page: 269 year: 1959 end-page: 271 ident: bib0014 article-title: A note on two problems in connection with graphs publication-title: Numerische Mathematik – volume: 8 start-page: 1643 year: 2008 end-page: 1653 ident: bib0051 article-title: Solving shortest path problem using particle swarm optimization publication-title: Applied Soft Computing – volume: 8 start-page: 204 year: 2004 end-page: 210 ident: bib0050 article-title: The fully informed particle swarm: Simpler, maybe better publication-title: IEEE Transactions on Evolutionary Computation – volume: 175 start-page: 367 year: 2010 end-page: 407 ident: bib0027 article-title: Variable neighborhood search: methods and applications publication-title: Annals of Operations Research – start-page: 313 year: 2008 end-page: 322 ident: bib0012 article-title: Discrete particle swarm optimization for the minimum labelling steiner tree problem publication-title: Nature inspired cooperative strategies for optimization (NICSO 2007) – volume: 14 start-page: 150 year: 2010 end-page: 169 ident: bib0037 article-title: Niching without niching parameters: Particle swarm optimization using a ring topology publication-title: IEEE Transactions on Evolutionary Computation – start-page: 174 year: 2003 end-page: 181 ident: bib0056 article-title: Fitness-distance-ratio based particle swarm optimization publication-title: Proceedings of the 2003 IEEE swarm intelligence symposium – start-page: 1677 year: 2002 end-page: 1681 ident: bib0028 article-title: Multiobjective optimization using dynamic neighborhood particle swarm optimization publication-title: Proceedings of the Congress Evolutionary Computation – year: 2004 ident: bib0015 article-title: Ant colony optimization: A bradford book – volume: 10 start-page: 293 year: 1980 end-page: 310 ident: bib0025 article-title: A dual algorithm for the constrained shortest path problem publication-title: Networks – volume: 7 start-page: 59 year: 2008 end-page: 78 ident: bib0043 article-title: A particle swarm optimization algorithm with path relinking for the location routing problem publication-title: Journal of Mathematical Modelling and Algorithms – volume: 1 start-page: 190 year: 1989 end-page: 206 ident: bib0021 article-title: Tabu search I publication-title: ORSA Journal on Computing – volume: 209 start-page: 16 year: 2012 end-page: 36 ident: bib0053 article-title: A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization publication-title: Information Sciences – volume: 6 start-page: 467 year: 2007 end-page: 484 ident: bib0002 article-title: A review of particle swarm optimization. part i: Background and development publication-title: Natural Computing – volume: 185 start-page: 1050 year: 2007 end-page: 1062 ident: bib0054 article-title: MCPSO: A multi-swarm cooperative particle swarm optimizer publication-title: Applied Mathematics and Computation – start-page: 1 year: 2003 end-page: 36 ident: bib0023 article-title: Scatter search and path relinking: Advances and applications publication-title: Handbook of metaheuristics – volume: 223 start-page: 119 year: 2013 end-page: 135 ident: bib0069 article-title: Diversity enhanced particle swarm optimization with neighborhood search publication-title: Information Sciences – volume: 1 start-page: 235 year: 2002 end-page: 306 ident: bib0055 article-title: Recent approaches to global optimization problems through particle swarm optimization publication-title: Natural Computing – start-page: 180 year: 2013 end-page: 187 ident: bib0067 article-title: A novel enhanced particle swarm optimization method with diversity and neighborhood search publication-title: Proceedings of the 2013 IEEE international conference on systems, man, and cybernetics (SMC2013) – start-page: 81 year: 2001 end-page: 86 ident: bib0016 article-title: Particle swarm optimization: Developments, applications and resources publication-title: IEEE Congress on Evolutionary Computation – volume: 2 start-page: 4 year: 1990 end-page: 32 ident: bib0022 article-title: Tabu search II publication-title: ORSA Journal on Computing – year: 1989 ident: bib0024 article-title: Genetic algorithms in search, optimization, and machine learning – volume: 40 start-page: 378 year: 2013 end-page: 384 ident: bib0042 article-title: On an exact method for the constrained shortest path problem publication-title: Computers and Operations Research – volume: 17 start-page: 1159 year: 2013 end-page: 1173 ident: bib0047 article-title: Particle swarm optimization with expanding neighborhood topology for the permutation flowshop scheduling problem publication-title: Soft Computing – volume: 53 start-page: 1174 year: 2006 end-page: 1187 ident: bib0070 article-title: Constrained shortest link-disjoint paths selection: A network programming based approach publication-title: IEEE Transactions on Circuits and Systems – volume: 41 start-page: 459 year: 2012 end-page: 472 ident: bib0019 article-title: Technology adoption and training practices as a constrained shortest path problem publication-title: Omega – volume: 14 start-page: 191 year: 1966 end-page: 197 ident: bib0031 article-title: The shortest route problem with constraints publication-title: Journal of Mathematical Analysis and Applications – volume: 10 start-page: 281 year: 2006 end-page: 295 ident: bib0038 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation – volume: 9 start-page: 29 year: 2010 end-page: 46 ident: bib0013 article-title: Discrete particle swarm optimization for the minimum labelling steiner tree problem publication-title: Natural Computing – volume: 41 start-page: 756 year: 2007 end-page: 771 ident: bib0060 article-title: An improved solution algorithm for the constrained shortest path problem publication-title: Transportation Research Part B: Methodological – volume: 1 start-page: 33 year: 2007 end-page: 57 ident: bib0057 article-title: Particle swarm optimization. an overview publication-title: Swarm Intelligence – year: 2007 ident: bib0017 article-title: Computational Intelligence: An introduction – volume: 220 start-page: 671 year: 1982 end-page: 680 ident: bib0035 article-title: Optimization by simulated annealing publication-title: Science – volume: 44 start-page: 34 year: 2013 end-page: 47 ident: bib0041 article-title: Bi-level programming based real-time path planning for unmanned aerial vehicles publication-title: Knowledge-Based Systems – volume: 24 start-page: 623 year: 2014 end-page: 642 ident: bib0039 article-title: Particle swarm optimization with adaptive time-varying topology connectivity publication-title: Applied Soft Computing – volume: 7832 start-page: 133 year: 2013 end-page: 144 ident: bib0046 article-title: Combinatorial neighborhood topology particle swarm optimization algorithm for the vehicle routing problem publication-title: Proceedings of the thirteenth European conference on evolutionary computation in combinatorial optimization (EVOCOP 2013) – volume: 182 start-page: 156 year: 2012 end-page: 168 ident: bib0020 article-title: Inter-particle communication and search-dynamics of lbest particle swarm optimizers: An analysis publication-title: Information Sciences – reference: Shi, Y., & Eberhart, R. C. (1998a). A modified particle swarm optimizer. Proceedings of the 1998 IEEE World Congress on Computational Intelligence, (pp. 69–73). – volume: 27 start-page: 80 year: 2014 end-page: 102 ident: bib0040 article-title: Particle swarm optimization with increasing topology connectivity publication-title: Engineering Applications of Artificial Intelligence – volume: 130 start-page: 449 year: 2001 end-page: 467 ident: bib0026 article-title: Variable neighborhood search: Principles and applications publication-title: European Journal of Operational Research – volume: 37 start-page: 432 year: 2010 end-page: 442 ident: bib0045 article-title: A hybrid multi-swarm particle swarm optimization algorithm for the probabilistic traveling salesman problem publication-title: Computers and Operations Research – volume: 7 start-page: 109 year: 2008 end-page: 124 ident: bib0003 article-title: A review of particle swarm optimization. part II: Hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications publication-title: Natural Computing – start-page: 1474 year: 2005 end-page: 1487 ident: bib0066 article-title: Darwinian particle swarm optimization publication-title: Proceedings of the second Indian international conference on artificial intelligence – volume: 35 start-page: 1272 year: 2005 end-page: 1282 ident: bib0029 article-title: A hierarchical particle swarm optimizer and its adaptive variant publication-title: IEEE Transactions on Systems, Man, and Cybernetics ? Part B: Cybernetics – volume: 189 start-page: 1859 year: 2007 end-page: 1883 ident: bib0007 article-title: Locating multiple optima using particle swarm optimization publication-title: Applied Mathematics and Computation – volume: 18 start-page: 1171 year: 2011 end-page: 1183 ident: bib0065 article-title: Modeling of vertical split rim cracking in railroad wheels publication-title: Engineering Failure Analysis – volume: 18 start-page: 3134 year: 2013 end-page: 3145 ident: bib0030 article-title: Particle swarm optimization with age-group topology for multimodal functions and data clustering publication-title: Communications in Nonlinear Science and Numerical Simulation – volume: 23 start-page: 463 year: 2010 end-page: 472 ident: bib0048 article-title: A hybrid particle swarm optimization algorithm for the vehicle routing problem publication-title: Engineering Applications of Artificial Intelligence – volume: 16 start-page: 593 year: 2010 end-page: 616 ident: bib0052 article-title: Hybrid co-evolutionary particle swarm optimization and noising metaheuristics for the delay constrained least cost path problem publication-title: Journal of Heuristics – volume: 6 start-page: 58 year: 2002 end-page: 73 ident: bib0011 article-title: The particle swarm: Explosion, stability and convergence in a multi-dimensional complex space publication-title: IEEE Transactions on Evolutionary Computation – year: 2005 ident: bib0058 article-title: Differential evolution: A practical approach to global optimization – volume: 18 start-page: 22 year: 2014 end-page: 37 ident: bib0006 article-title: A hybrid particle swarm with a time-adaptive topology for constrained optimization publication-title: Swarm and Evolutionary Computation – volume: 12 start-page: 2790 year: 2012 end-page: 2800 ident: bib0008 article-title: Using computational intelligence for large scale air route networks design publication-title: Applied Soft Computing – volume: 40 start-page: 7607 year: 2013 end-page: 7616 ident: bib0071 article-title: An adaptive amoeba algorithm for constrained shortest paths publication-title: Expert Systems with Applications – year: 2006 ident: bib0010 article-title: Particle swarm optimization – volume: 142 start-page: 221 year: 2002 end-page: 230 ident: bib0001 article-title: A penalty function heuristic for the resource constrained shortest path problem publication-title: European Journal of Operational Research – volume: 23 start-page: 3 year: 2013 end-page: 17 ident: bib0063 article-title: Minimum cost network flows: Problems, algorithms, and software publication-title: Yugoslav Journal of Operations Research – volume: 14 start-page: 31 year: 2009 end-page: 52 ident: bib0059 article-title: Routing military aircraft with a constrained shortest-path algorithm publication-title: Military Operations Research – reference: Kennedy, J., & Mendes, R. (2002). Population structure and particle swarm performance. Proceedings of the 2002 IEEE congress on evolutionary computation, (pp. 1671–1676). – start-page: 1958 year: 1999 end-page: 1962 ident: bib0064 article-title: Particle swarm optimiser with neighborhood operator publication-title: Proceedings of the 1999 IEEE congress on evolutionary computation – volume: 19 start-page: 379 year: 1989 end-page: 394 ident: bib0004 article-title: An algorithm for the resource constrained shortest path problem publication-title: Networks – volume: 7832 start-page: 591 year: 1998 end-page: 600 ident: bib0062 article-title: Parameter selection in particle swarm optimization publication-title: Evolutionary programming VII – volume: 2011 start-page: 42 year: 2011 end-page: 53 ident: bib0036 article-title: Route finder: efficiently finding publication-title: Principles and Practice of Constraint Programming (CP) – volume: 40 start-page: 3595 year: 2013 end-page: 3605 ident: bib0049 article-title: Synthesis of fixed-structure robust controllers using a constrained particle swarm optimizer with cyclic neighborhood topology publication-title: Expert Systems with Applications – volume: 6 start-page: 109 year: 1995 end-page: 133 ident: bib0018 article-title: Greedy randomized adaptive search procedure publication-title: Journal of Global Optimization – volume: 37 start-page: 1446 year: 2010 end-page: 1455 ident: bib0044 article-title: A hybrid genetic – Particle swarm optimization algorithm for the vehicle routing problem publication-title: Expert Systems with Applications – volume: 2014 start-page: 271280 year: 2014 ident: bib0068 article-title: A bio-inspired method for the constrained shortest path problem publication-title: The Scientific World Journal – volume: 8 start-page: 1643 issue: 4 year: 2008 ident: 10.1016/j.ejor.2017.03.031_bib0051 article-title: Solving shortest path problem using particle swarm optimization publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2008.01.002 – volume: 40 start-page: 3595 issue: 9 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0049 article-title: Synthesis of fixed-structure robust controllers using a constrained particle swarm optimizer with cyclic neighborhood topology publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2012.12.066 – volume: 142 start-page: 221 year: 2002 ident: 10.1016/j.ejor.2017.03.031_bib0001 article-title: A penalty function heuristic for the resource constrained shortest path problem publication-title: European Journal of Operational Research doi: 10.1016/S0377-2217(02)00262-X – start-page: 174 year: 2003 ident: 10.1016/j.ejor.2017.03.031_bib0056 article-title: Fitness-distance-ratio based particle swarm optimization – volume: 7 start-page: 109 year: 2008 ident: 10.1016/j.ejor.2017.03.031_bib0003 article-title: A review of particle swarm optimization. part II: Hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications publication-title: Natural Computing doi: 10.1007/s11047-007-9050-z – volume: 41 start-page: 459 year: 2012 ident: 10.1016/j.ejor.2017.03.031_bib0019 article-title: Technology adoption and training practices as a constrained shortest path problem publication-title: Omega doi: 10.1016/j.omega.2012.02.002 – volume: 37 start-page: 1446 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0044 article-title: A hybrid genetic – Particle swarm optimization algorithm for the vehicle routing problem publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2009.06.085 – volume: 40 start-page: 378 issue: 1 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0042 article-title: On an exact method for the constrained shortest path problem publication-title: Computers and Operations Research doi: 10.1016/j.cor.2012.07.008 – volume: 53 start-page: 1174 issue: 5 year: 2006 ident: 10.1016/j.ejor.2017.03.031_bib0070 article-title: Constrained shortest link-disjoint paths selection: A network programming based approach publication-title: IEEE Transactions on Circuits and Systems doi: 10.1109/TCSI.2006.869907 – volume: 7832 start-page: 133 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0046 article-title: Combinatorial neighborhood topology particle swarm optimization algorithm for the vehicle routing problem – year: 2005 ident: 10.1016/j.ejor.2017.03.031_bib0058 – volume: 23 start-page: 3 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0063 article-title: Minimum cost network flows: Problems, algorithms, and software publication-title: Yugoslav Journal of Operations Research doi: 10.2298/YJOR121120001S – volume: 220 start-page: 671 year: 1982 ident: 10.1016/j.ejor.2017.03.031_bib0035 article-title: Optimization by simulated annealing publication-title: Science doi: 10.1126/science.220.4598.671 – volume: 6 start-page: 109 year: 1995 ident: 10.1016/j.ejor.2017.03.031_bib0018 article-title: Greedy randomized adaptive search procedure publication-title: Journal of Global Optimization doi: 10.1007/BF01096763 – volume: 18 start-page: 22 year: 2014 ident: 10.1016/j.ejor.2017.03.031_bib0006 article-title: A hybrid particle swarm with a time-adaptive topology for constrained optimization publication-title: Swarm and Evolutionary Computation doi: 10.1016/j.swevo.2014.06.001 – ident: 10.1016/j.ejor.2017.03.031_bib0061 doi: 10.1109/ICEC.1998.699146 – volume: 182 start-page: 156 year: 2012 ident: 10.1016/j.ejor.2017.03.031_bib0020 article-title: Inter-particle communication and search-dynamics of lbest particle swarm optimizers: An analysis publication-title: Information Sciences doi: 10.1016/j.ins.2010.10.015 – volume: 6 start-page: 467 issue: 4 year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0002 article-title: A review of particle swarm optimization. part i: Background and development publication-title: Natural Computing doi: 10.1007/s11047-007-9049-5 – volume: 4 start-page: 1942 year: 1995 ident: 10.1016/j.ejor.2017.03.031_bib0033 article-title: Particle swarm optimization publication-title: Proceedings of the IEEE International Conference on Neural Networks doi: 10.1109/ICNN.1995.488968 – start-page: 1391 year: 1999 ident: 10.1016/j.ejor.2017.03.031_bib0032 article-title: Small worlds and mega-minds: Effects of neighborhood topology on particle swarm performance publication-title: Proceedings of IEEE Congress on Evolutionary Computation – start-page: 81 year: 2001 ident: 10.1016/j.ejor.2017.03.031_bib0016 article-title: Particle swarm optimization: Developments, applications and resources publication-title: IEEE Congress on Evolutionary Computation – start-page: 313 year: 2008 ident: 10.1016/j.ejor.2017.03.031_bib0012 article-title: Discrete particle swarm optimization for the minimum labelling steiner tree problem – volume: 1 start-page: 190 issue: 3 year: 1989 ident: 10.1016/j.ejor.2017.03.031_bib0021 article-title: Tabu search I publication-title: ORSA Journal on Computing doi: 10.1287/ijoc.1.3.190 – volume: 18 start-page: 1171 issue: 4 year: 2011 ident: 10.1016/j.ejor.2017.03.031_bib0065 article-title: Modeling of vertical split rim cracking in railroad wheels publication-title: Engineering Failure Analysis doi: 10.1016/j.engfailanal.2011.02.008 – volume: 23 start-page: 463 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0048 article-title: A hybrid particle swarm optimization algorithm for the vehicle routing problem publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2010.02.002 – volume: 14 start-page: 191 issue: 2 year: 1966 ident: 10.1016/j.ejor.2017.03.031_bib0031 article-title: The shortest route problem with constraints publication-title: Journal of Mathematical Analysis and Applications doi: 10.1016/0022-247X(66)90020-5 – volume: 2 start-page: 4 issue: 1 year: 1990 ident: 10.1016/j.ejor.2017.03.031_bib0022 article-title: Tabu search II publication-title: ORSA Journal on Computing doi: 10.1287/ijoc.2.1.4 – year: 2004 ident: 10.1016/j.ejor.2017.03.031_bib0015 – volume: 130 start-page: 449 year: 2001 ident: 10.1016/j.ejor.2017.03.031_bib0026 article-title: Variable neighborhood search: Principles and applications publication-title: European Journal of Operational Research doi: 10.1016/S0377-2217(00)00100-4 – volume: 7832 start-page: 591 year: 1998 ident: 10.1016/j.ejor.2017.03.031_bib0062 article-title: Parameter selection in particle swarm optimization – volume: 14 start-page: 150 issue: 1 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0037 article-title: Niching without niching parameters: Particle swarm optimization using a ring topology publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2009.2026270 – volume: 27 start-page: 80 year: 2014 ident: 10.1016/j.ejor.2017.03.031_bib0040 article-title: Particle swarm optimization with increasing topology connectivity publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2013.09.011 – volume: 24 start-page: 623 year: 2014 ident: 10.1016/j.ejor.2017.03.031_bib0039 article-title: Particle swarm optimization with adaptive time-varying topology connectivity publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2014.08.013 – volume: 189 start-page: 1859 year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0007 article-title: Locating multiple optima using particle swarm optimization publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2006.12.066 – volume: 2011 start-page: 42 year: 2011 ident: 10.1016/j.ejor.2017.03.031_bib0036 article-title: Route finder: efficiently finding k shortest paths using constraint programming publication-title: Principles and Practice of Constraint Programming (CP) – volume: 17 start-page: 1159 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0047 article-title: Particle swarm optimization with expanding neighborhood topology for the permutation flowshop scheduling problem publication-title: Soft Computing doi: 10.1007/s00500-013-0992-z – volume: 11 start-page: 4135 issue: 6 year: 2011 ident: 10.1016/j.ejor.2017.03.031_bib0005 article-title: Hybrid metaheuristics in combinatorial optimization: A survey publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2011.02.032 – volume: 35 start-page: 1272 issue: 6 year: 2005 ident: 10.1016/j.ejor.2017.03.031_bib0029 article-title: A hierarchical particle swarm optimizer and its adaptive variant publication-title: IEEE Transactions on Systems, Man, and Cybernetics ? Part B: Cybernetics doi: 10.1109/TSMCB.2005.850530 – start-page: 1 year: 2003 ident: 10.1016/j.ejor.2017.03.031_bib0023 article-title: Scatter search and path relinking: Advances and applications – volume: 16 start-page: 593 issue: 4 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0052 article-title: Hybrid co-evolutionary particle swarm optimization and noising metaheuristics for the delay constrained least cost path problem publication-title: Journal of Heuristics doi: 10.1007/s10732-009-9109-3 – volume: 175 start-page: 367 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0027 article-title: Variable neighborhood search: methods and applications publication-title: Annals of Operations Research doi: 10.1007/s10479-009-0657-6 – start-page: 1474 year: 2005 ident: 10.1016/j.ejor.2017.03.031_bib0066 article-title: Darwinian particle swarm optimization – volume: 12 start-page: 2790 issue: 9 year: 2012 ident: 10.1016/j.ejor.2017.03.031_bib0008 article-title: Using computational intelligence for large scale air route networks design publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2012.03.063 – volume: 6 start-page: 58 year: 2002 ident: 10.1016/j.ejor.2017.03.031_bib0011 article-title: The particle swarm: Explosion, stability and convergence in a multi-dimensional complex space publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.985692 – volume: 44 start-page: 34 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0041 article-title: Bi-level programming based real-time path planning for unmanned aerial vehicles publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2013.01.011 – volume: 10 start-page: 281 issue: 3 year: 2006 ident: 10.1016/j.ejor.2017.03.031_bib0038 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2005.857610 – volume: 1 start-page: 33 year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0057 article-title: Particle swarm optimization. an overview publication-title: Swarm Intelligence doi: 10.1007/s11721-007-0002-0 – volume: 209 start-page: 16 year: 2012 ident: 10.1016/j.ejor.2017.03.031_bib0053 article-title: A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization publication-title: Information Sciences doi: 10.1016/j.ins.2012.04.028 – volume: 185 start-page: 1050 year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0054 article-title: MCPSO: A multi-swarm cooperative particle swarm optimizer publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2006.07.026 – volume: 9 start-page: 29 issue: 1 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0013 article-title: Discrete particle swarm optimization for the minimum labelling steiner tree problem publication-title: Natural Computing doi: 10.1007/s11047-009-9137-9 – volume: 18 start-page: 3134 issue: 11 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0030 article-title: Particle swarm optimization with age-group topology for multimodal functions and data clustering publication-title: Communications in Nonlinear Science and Numerical Simulation doi: 10.1016/j.cnsns.2013.03.011 – volume: 223 start-page: 119 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0069 article-title: Diversity enhanced particle swarm optimization with neighborhood search publication-title: Information Sciences doi: 10.1016/j.ins.2012.10.012 – year: 1989 ident: 10.1016/j.ejor.2017.03.031_bib0024 – volume: 7 start-page: 59 issue: 1 year: 2008 ident: 10.1016/j.ejor.2017.03.031_bib0043 article-title: A particle swarm optimization algorithm with path relinking for the location routing problem publication-title: Journal of Mathematical Modelling and Algorithms doi: 10.1007/s10852-007-9073-6 – volume: 1 start-page: 269 year: 1959 ident: 10.1016/j.ejor.2017.03.031_bib0014 article-title: A note on two problems in connection with graphs publication-title: Numerische Mathematik doi: 10.1007/BF01386390 – volume: 40 start-page: 7607 issue: 18 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0071 article-title: An adaptive amoeba algorithm for constrained shortest paths publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2013.07.054 – start-page: 180 year: 2013 ident: 10.1016/j.ejor.2017.03.031_bib0067 article-title: A novel enhanced particle swarm optimization method with diversity and neighborhood search – start-page: 1958 year: 1999 ident: 10.1016/j.ejor.2017.03.031_bib0064 article-title: Particle swarm optimiser with neighborhood operator – volume: 19 start-page: 379 year: 1989 ident: 10.1016/j.ejor.2017.03.031_bib0004 article-title: An algorithm for the resource constrained shortest path problem publication-title: Networks doi: 10.1002/net.3230190402 – volume: 1 start-page: 235 issue: 2–3 year: 2002 ident: 10.1016/j.ejor.2017.03.031_bib0055 article-title: Recent approaches to global optimization problems through particle swarm optimization publication-title: Natural Computing doi: 10.1023/A:1016568309421 – volume: 2014 start-page: 271280 year: 2014 ident: 10.1016/j.ejor.2017.03.031_sbref0066 article-title: A bio-inspired method for the constrained shortest path problem publication-title: The Scientific World Journal – volume: 52 start-page: 256 issue: 4 year: 2008 ident: 10.1016/j.ejor.2017.03.031_bib0009 article-title: Lagrangian relaxation and enumeration for solving constrained shortest-path problems publication-title: Networks doi: 10.1002/net.20247 – volume: 41 start-page: 756 issue: 7 year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0060 article-title: An improved solution algorithm for the constrained shortest path problem publication-title: Transportation Research Part B: Methodological doi: 10.1016/j.trb.2006.12.001 – ident: 10.1016/j.ejor.2017.03.031_bib0034 doi: 10.1109/CEC.2002.1004493 – year: 2007 ident: 10.1016/j.ejor.2017.03.031_bib0017 – start-page: 1677 year: 2002 ident: 10.1016/j.ejor.2017.03.031_bib0028 article-title: Multiobjective optimization using dynamic neighborhood particle swarm optimization publication-title: Proceedings of the Congress Evolutionary Computation – volume: 37 start-page: 432 year: 2010 ident: 10.1016/j.ejor.2017.03.031_bib0045 article-title: A hybrid multi-swarm particle swarm optimization algorithm for the probabilistic traveling salesman problem publication-title: Computers and Operations Research doi: 10.1016/j.cor.2009.03.004 – volume: 14 start-page: 31 issue: 3 year: 2009 ident: 10.1016/j.ejor.2017.03.031_bib0059 article-title: Routing military aircraft with a constrained shortest-path algorithm publication-title: Military Operations Research doi: 10.5711/morj.14.3.31 – year: 2006 ident: 10.1016/j.ejor.2017.03.031_sbref0010 – volume: 10 start-page: 293 year: 1980 ident: 10.1016/j.ejor.2017.03.031_bib0025 article-title: A dual algorithm for the constrained shortest path problem publication-title: Networks doi: 10.1002/net.3230100403 – volume: 8 start-page: 204 issue: 3 year: 2004 ident: 10.1016/j.ejor.2017.03.031_bib0050 article-title: The fully informed particle swarm: Simpler, maybe better publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2004.826074 |
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| Snippet | •The Constrained Shortest Path problem is solved using a hybridized version of PSO.•A different equation for the particles’ velocities is used.•A novel... In this paper, a well known NP-hard problem, the constrained shortest path problem, is studied. As efficient metaheuristic approaches are required for its... |
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| SubjectTerms | Constrained Shortest Path problem Expanding neighborhood topology Industrial Logistics Industriell logistik Particle Swarm Optimization Variable Neighborhood Search |
| Title | A hybrid Particle Swarm Optimization – Variable Neighborhood Search algorithm for Constrained Shortest Path problems |
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