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Published in: Wireless Networks 7/2020

15-12-2018

Approximating the Pareto front of a bi-objective problem in telecommunication networks using a co-evolutionary algorithm

Authors: José-Fernando Camacho-Vallejo, Cristóbal Garcia-Reyes

Published in: Wireless Networks | Issue 7/2020

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Abstract

This paper studies a telecommunication network design problem. In this network, users must be connected to capacitated hubs. Then, hubs that concentrate users must be connected to each other and possibly to other hubs with no users. The connections in the network must lead to a tree topology. Hence, connection between hubs can be considered as looking for forming a Steiner tree. This problem is modeled as a bi-objective mathematical programming problem. One objective function minimizes user’s latency with respect to the information packages flowing through the capacitated hubs, and the other objective function aims the minimization of the total network’s connection cost. To approximate the Pareto front of this bi-objective problem, a co-evolutionary algorithm is developed. In the proposed algorithm, two populations are considered. Each population is associated with one objective function. The co-evolutionary operator consists of an information exchange between both populations that occurs after the genetic operators have been applied. As a result of this co-evolutionary operator, the non-dominated solutions are identified. Computational experimentation shows that the approximated Pareto fronts are representative despite their non-convexity, and they contain a sufficient number of non-dominated solutions over the tested instances. Also, the kth distance among non-dominated solutions is relatively small, which indicates that the approximated Pareto fronts are dense. Furthermore, the required computational time is very small for a problem with the characteristics herein considered.

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Literature
1.
go back to reference Van Hoesel, S. (2005). Optimization in telecommunication networks. Statistica Neerlandica, 59(2), 180–205.MathSciNetMATH Van Hoesel, S. (2005). Optimization in telecommunication networks. Statistica Neerlandica, 59(2), 180–205.MathSciNetMATH
2.
go back to reference Corne, D., Oates, M. J., & Smith, G. D. (Eds.). (2000). Telecommunications optimization: Heuristics and adaptive techniques. New York: Wiley. Corne, D., Oates, M. J., & Smith, G. D. (Eds.). (2000). Telecommunications optimization: Heuristics and adaptive techniques. New York: Wiley.
3.
go back to reference Vasant, P., Litvinchev, I., & Marmolejo-Saucedo, J. A. (Eds.). (2017). Modeling, simulation, and optimization. Berlin: Springer. Vasant, P., Litvinchev, I., & Marmolejo-Saucedo, J. A. (Eds.). (2017). Modeling, simulation, and optimization. Berlin: Springer.
4.
go back to reference Minoux, M. (1989). Networks synthesis and optimum network design problems: Models, solution methods and applications. Networks, 19(3), 313–360.MathSciNetMATH Minoux, M. (1989). Networks synthesis and optimum network design problems: Models, solution methods and applications. Networks, 19(3), 313–360.MathSciNetMATH
6.
go back to reference Du, D. Z., Lu, B., Ngo, H., & Pardalos, P. M. (2009). Steiner tree problems. In C. A. Floudas & P. M. Pardalos (Eds.), Encyclopedia of optimization (2nd ed.). Berlin: Springer. Du, D. Z., Lu, B., Ngo, H., & Pardalos, P. M. (2009). Steiner tree problems. In C. A. Floudas & P. M. Pardalos (Eds.), Encyclopedia of optimization (2nd ed.). Berlin: Springer.
7.
go back to reference Dror, M., & Haouari, M. (2000). Generalized Steiner problems and other variants. Journal of Combinatorial Optimization, 4, 415–436.MathSciNetMATH Dror, M., & Haouari, M. (2000). Generalized Steiner problems and other variants. Journal of Combinatorial Optimization, 4, 415–436.MathSciNetMATH
8.
go back to reference Biniaz, A., Maheshwari, A., & Smid, M. (2015). On the hardness of full Steiner tree problems. Journal of Discrete Algorithms, 34, 118–127.MathSciNetMATH Biniaz, A., Maheshwari, A., & Smid, M. (2015). On the hardness of full Steiner tree problems. Journal of Discrete Algorithms, 34, 118–127.MathSciNetMATH
9.
go back to reference Khuller, S., & Zhu, A. (2002). The general Steiner tree-star problem. Information Processing Letters, 84, 215–220.MathSciNetMATH Khuller, S., & Zhu, A. (2002). The general Steiner tree-star problem. Information Processing Letters, 84, 215–220.MathSciNetMATH
10.
go back to reference Marmolejo, J. A., Litvinchev, I., Aceves, R., & Ramirez, J. M. (2011). Multiperiod optimal planning of thermal generation using cross decomposition. Journal of Computer and Systems Sciences International, 50(5), 793–804.MathSciNetMATH Marmolejo, J. A., Litvinchev, I., Aceves, R., & Ramirez, J. M. (2011). Multiperiod optimal planning of thermal generation using cross decomposition. Journal of Computer and Systems Sciences International, 50(5), 793–804.MathSciNetMATH
11.
go back to reference Voss, S. (1992). Steiner’s problem in graphs: Heuristic methods. Discrete Applied Mathematics, 40, 45–72.MathSciNetMATH Voss, S. (1992). Steiner’s problem in graphs: Heuristic methods. Discrete Applied Mathematics, 40, 45–72.MathSciNetMATH
12.
go back to reference Plesník, J. (1992). Heuristics for the Steiner problem in graphs. Discrete Applied Mathematics, 37, 451–463.MathSciNetMATH Plesník, J. (1992). Heuristics for the Steiner problem in graphs. Discrete Applied Mathematics, 37, 451–463.MathSciNetMATH
13.
go back to reference Martins, S. L., Ribeiro, C., & Souza, M. (1998). A parallel GRASP for the Steiner problem in graphs. In A. Ferreira, & J. Rolim, (Eds.), Proceedings of IRREGULAR98 5th international symposium on solving irregularly structured problems in parallel, vol. 1457 of lecture notes in computer science (pp. 285–297). Berlin: Springer. Martins, S. L., Ribeiro, C., & Souza, M. (1998). A parallel GRASP for the Steiner problem in graphs. In A. Ferreira, & J. Rolim, (Eds.), Proceedings of IRREGULAR98 5th international symposium on solving irregularly structured problems in parallel, vol. 1457 of lecture notes in computer science (pp. 285–297). Berlin: Springer.
14.
go back to reference Consoli, S., Pérez, J. M., Darby-Dowman, K., & Mladenović, N. (2008). Discrete particle swarm optimization for the minimum labelling Steiner tree problem. In Nature inspired cooperative strategies for optimization (NICSO 2007) (pp. 313–322). Berlin: Springer. Consoli, S., Pérez, J. M., Darby-Dowman, K., & Mladenović, N. (2008). Discrete particle swarm optimization for the minimum labelling Steiner tree problem. In Nature inspired cooperative strategies for optimization (NICSO 2007) (pp. 313–322). Berlin: Springer.
15.
go back to reference Ribeiro, C. C., & De Souza, M. C. (2000). Tabu search for the Steiner problem in graphs. Networks: An International Journal, 36(2), 138–146.MathSciNetMATH Ribeiro, C. C., & De Souza, M. C. (2000). Tabu search for the Steiner problem in graphs. Networks: An International Journal, 36(2), 138–146.MathSciNetMATH
16.
go back to reference Gendreau, M., Larochelle, J. F., & Sanso, B. (1999). A tabu search heuristic for the Steiner tree problem. Networks: An International Journal, 34(2), 162–172.MathSciNetMATH Gendreau, M., Larochelle, J. F., & Sanso, B. (1999). A tabu search heuristic for the Steiner tree problem. Networks: An International Journal, 34(2), 162–172.MathSciNetMATH
17.
go back to reference Bastos, M. P., & Ribeiro, C. C. (2002). Reactive tabu search with path-relinking for the Steiner problem in graphs. In C. C. Ribeiro, & P. Hansen (Eds.), Essays and surveys in metaheuristics. Operations research/computer science interfaces series (Vol. 15, pp. 39–58). Boston, MA: Springer. Bastos, M. P., & Ribeiro, C. C. (2002). Reactive tabu search with path-relinking for the Steiner problem in graphs. In C. C. Ribeiro, & P. Hansen (Eds.), Essays and surveys in metaheuristics. Operations research/computer science interfaces series (Vol. 15, pp. 39–58). Boston, MA: Springer.
18.
go back to reference Consoli, S., Darby-Dowman, K., Mladenović, N., & Moreno-Pérez, J. A. (2009). Variable neighbourhood search for the minimum labelling Steiner tree problem. Annals of Operations Research, 172(1), 71–96.MathSciNetMATH Consoli, S., Darby-Dowman, K., Mladenović, N., & Moreno-Pérez, J. A. (2009). Variable neighbourhood search for the minimum labelling Steiner tree problem. Annals of Operations Research, 172(1), 71–96.MathSciNetMATH
19.
go back to reference Camacho-Vallejo, J.-F., Mar-Ortiz, J., López-Ramos, F., & Rodríguez, R. P. (2015). A genetic algorithm for the bi-level topological design of local area networks. PLoS ONE, 10(6), 1–21. Camacho-Vallejo, J.-F., Mar-Ortiz, J., López-Ramos, F., & Rodríguez, R. P. (2015). A genetic algorithm for the bi-level topological design of local area networks. PLoS ONE, 10(6), 1–21.
20.
go back to reference Dehouche, N. (2018). Devolutionary genetic algorithms with application to the minimum labeling Steiner tree problem. Evolving Systems, 9, 157–168. Dehouche, N. (2018). Devolutionary genetic algorithms with application to the minimum labeling Steiner tree problem. Evolving Systems, 9, 157–168.
21.
go back to reference Liu, L., Song, Y., Zhang, H., Ma, H., & Vasilakos, A. V. (2015). Physarum optimization: A biology-inspired algorithm for the Steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 818–831.MathSciNetMATH Liu, L., Song, Y., Zhang, H., Ma, H., & Vasilakos, A. V. (2015). Physarum optimization: A biology-inspired algorithm for the Steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 818–831.MathSciNetMATH
22.
go back to reference Gouveia, L., Leitner, M., & Ljubić, I. (2014). Hop constrained Steiner trees with multiple root nodes. European Journal of Operational Research, 236, 100–112.MathSciNetMATH Gouveia, L., Leitner, M., & Ljubić, I. (2014). Hop constrained Steiner trees with multiple root nodes. European Journal of Operational Research, 236, 100–112.MathSciNetMATH
23.
go back to reference Fu, Z.-H., & Hao, J.-K. (2014). Breakout local search for the Steiner tree problem with revenue, budget and hop constraints. European Journal of Operational Research, 232, 209–220.MathSciNetMATH Fu, Z.-H., & Hao, J.-K. (2014). Breakout local search for the Steiner tree problem with revenue, budget and hop constraints. European Journal of Operational Research, 232, 209–220.MathSciNetMATH
24.
go back to reference Leggieri, V., Haouari, M., & Triki, Ch. (2014). The Steiner tree problem with delays: A compact formulation and reduction procedures. Discrete Applied Mathematics, 164, 178–190.MathSciNetMATH Leggieri, V., Haouari, M., & Triki, Ch. (2014). The Steiner tree problem with delays: A compact formulation and reduction procedures. Discrete Applied Mathematics, 164, 178–190.MathSciNetMATH
25.
go back to reference DiPuglia, L., Gaudioso, M., Guerriero, F., & Miglionico, G. (2018). A Lagrangean-based decomposition approach for the link constrained Steiner tree problem. Optimization Methods and Software, 33(3), 650–670.MathSciNetMATH DiPuglia, L., Gaudioso, M., Guerriero, F., & Miglionico, G. (2018). A Lagrangean-based decomposition approach for the link constrained Steiner tree problem. Optimization Methods and Software, 33(3), 650–670.MathSciNetMATH
26.
go back to reference Xu, J., Chiu, S. Y., & Glover, F. (1996). Using tabu search to solve the Steiner tree-star problem in telecommunications network design. Telecommunication Systems, 6, 117–125. Xu, J., Chiu, S. Y., & Glover, F. (1996). Using tabu search to solve the Steiner tree-star problem in telecommunications network design. Telecommunication Systems, 6, 117–125.
27.
go back to reference Lee, Y., Lu, L., & Qiu, Y. (1994). Strong formulations and cutting planes for designing digital data service networks. Telecommunication Systems, 2, 261–274. Lee, Y., Lu, L., & Qiu, Y. (1994). Strong formulations and cutting planes for designing digital data service networks. Telecommunication Systems, 2, 261–274.
28.
go back to reference Clarke, L. W., & Anandalingam, G. (1996). An integrated system for designing minimum cost survivable telecommunications networks. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 26(6), 856–862. Clarke, L. W., & Anandalingam, G. (1996). An integrated system for designing minimum cost survivable telecommunications networks. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 26(6), 856–862.
29.
go back to reference Ersoy, C., & Panwar, S. S. (1993). Topological design of interconnected LAN/MAN networks. IEEE Journal on Selected Areas in Communications, 2(8), 1172–1182. Ersoy, C., & Panwar, S. S. (1993). Topological design of interconnected LAN/MAN networks. IEEE Journal on Selected Areas in Communications, 2(8), 1172–1182.
30.
go back to reference Girard, A. (1993). Revenue optimization of telecommunication networks. IEEE Transactions on Communications, 41(4), 583–591.MATH Girard, A. (1993). Revenue optimization of telecommunication networks. IEEE Transactions on Communications, 41(4), 583–591.MATH
31.
go back to reference Chen, D., Du, D. Z., Hu, X. D., Lin, G. H., Wang, L., & Xue, G. (2000). Approximations for Steiner trees with minimum number of Steiner points. Journal of Global Optimization, 18(1), 17–33.MathSciNetMATH Chen, D., Du, D. Z., Hu, X. D., Lin, G. H., Wang, L., & Xue, G. (2000). Approximations for Steiner trees with minimum number of Steiner points. Journal of Global Optimization, 18(1), 17–33.MathSciNetMATH
32.
go back to reference Orlowski, S., & Wessaly, R. (2006). The effect of hop limits on optimal cost in survivable network design. In S. Raghavan, & G. Anandalingam (Eds.) Telecommunications planning: Innovations in pricing, network design and management. Operations research/computer science interfaces series (Vol. 33, pp. 151–166). Boston, MA: Springer. Orlowski, S., & Wessaly, R. (2006). The effect of hop limits on optimal cost in survivable network design. In S. Raghavan, & G. Anandalingam (Eds.) Telecommunications planning: Innovations in pricing, network design and management. Operations research/computer science interfaces series (Vol. 33, pp. 151–166). Boston, MA: Springer.
33.
go back to reference Sitters, R. (2002). The minimum latency problem is NP-hard for weighted trees. In International conference on integer programming and combinatorial optimization (pp. 230–239), Berlin: Springer. Sitters, R. (2002). The minimum latency problem is NP-hard for weighted trees. In International conference on integer programming and combinatorial optimization (pp. 230–239), Berlin: Springer.
34.
go back to reference Martins, S. L., & Ferreira, N. G. (2011). A bi-criteria approach for Steiner’s tree problems in communication networks. In U. Krieger, & P. Van Mieghem (Eds.), Proceedings of international workshop on modeling, analysis and control of complex networks, ITCP (International Teletraffic Congress, San Francisco) (pp. 37–44). Martins, S. L., & Ferreira, N. G. (2011). A bi-criteria approach for Steiner’s tree problems in communication networks. In U. Krieger, & P. Van Mieghem (Eds.), Proceedings of international workshop on modeling, analysis and control of complex networks, ITCP (International Teletraffic Congress, San Francisco) (pp. 37–44).
35.
go back to reference Marathe, M. V., Ravi, R., Sundaram, R., Ravi, S. S., Rosenkrantz, D. J., & Hunt, H. B, I. I. I. (1998). Bicriteria network design problems. Journal of Algorithms, 28(1), 142–171.MathSciNetMATH Marathe, M. V., Ravi, R., Sundaram, R., Ravi, S. S., Rosenkrantz, D. J., & Hunt, H. B, I. I. I. (1998). Bicriteria network design problems. Journal of Algorithms, 28(1), 142–171.MathSciNetMATH
36.
go back to reference Potter, M. A. (1997). The design and analysis of a computational model of cooperative co-evolution, Ph.D. Thesis, George Mason University. Potter, M. A. (1997). The design and analysis of a computational model of cooperative co-evolution, Ph.D. Thesis, George Mason University.
37.
go back to reference Venter, G., & Haftka, R. T. (1996). A two species genetic algorithm for designing composite laminates subjected to uncertainty. In Proceedings of 37th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference (pp. 1848–1857). Venter, G., & Haftka, R. T. (1996). A two species genetic algorithm for designing composite laminates subjected to uncertainty. In Proceedings of 37th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference (pp. 1848–1857).
38.
go back to reference Sun, Y., Zhang, L., & Gu, X. (2012). A hybrid co-evolutionary cultural algorithm based on particle swarm optimization for solving global optimization problems. Neurocomputing, 98, 76–89. Sun, Y., Zhang, L., & Gu, X. (2012). A hybrid co-evolutionary cultural algorithm based on particle swarm optimization for solving global optimization problems. Neurocomputing, 98, 76–89.
39.
go back to reference Goh, C. K., Tan, K. C., Liu, D. S., & Chiam, S. C. (2010). A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design. European Journal of Operational Research, 202(1), 42–54.MATH Goh, C. K., Tan, K. C., Liu, D. S., & Chiam, S. C. (2010). A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design. European Journal of Operational Research, 202(1), 42–54.MATH
40.
go back to reference Gen, M., Kumar, A., & Kim, J. R. (2005). Recent network design techniques using evolutionary algorithms. International Journal of Production Economics, 98(2), 251–261. Gen, M., Kumar, A., & Kim, J. R. (2005). Recent network design techniques using evolutionary algorithms. International Journal of Production Economics, 98(2), 251–261.
41.
go back to reference Wang, X., Wang, S., & Ma, J. J. (2007). An improved co-evolutionary particle swarm optimization for wireless sensor networks with dynamic deployment. Sensors, 7(3), 354–370. Wang, X., Wang, S., & Ma, J. J. (2007). An improved co-evolutionary particle swarm optimization for wireless sensor networks with dynamic deployment. Sensors, 7(3), 354–370.
42.
go back to reference Casas-Ramírez, M. S., & Camacho-Vallejo, J. F. (2017). Solving the p-median bilevel problem with order through a hybrid heuristic. Applied Soft Computing, 60, 73–86. Casas-Ramírez, M. S., & Camacho-Vallejo, J. F. (2017). Solving the p-median bilevel problem with order through a hybrid heuristic. Applied Soft Computing, 60, 73–86.
43.
go back to reference Kim, J. R., Lee, J. U., & Jo, J. B. (2009). Hierarchical spanning tree network design with Nash genetic algorithm. Computers & Industrial Engineering, 56(3), 1040–1052. Kim, J. R., Lee, J. U., & Jo, J. B. (2009). Hierarchical spanning tree network design with Nash genetic algorithm. Computers & Industrial Engineering, 56(3), 1040–1052.
44.
go back to reference Sipper, M., Fu, W., Ahuja, K., & Moore, J. H. (2018). Investigating the parameter space of evolutionary algorithms. BioData Mining, 11(2), 2–14. Sipper, M., Fu, W., Ahuja, K., & Moore, J. H. (2018). Investigating the parameter space of evolutionary algorithms. BioData Mining, 11(2), 2–14.
45.
go back to reference Martí, R., González-Velarde, J. L., & Duarte, A. (2009). Heuristics for the bi-objective path dissimilarity problem. Computers & Operations Research, 36(11), 2905–2912.MATH Martí, R., González-Velarde, J. L., & Duarte, A. (2009). Heuristics for the bi-objective path dissimilarity problem. Computers & Operations Research, 36(11), 2905–2912.MATH
46.
go back to reference Bard, J. F. (1998). Practical bilevel optimization: Algorithms and applications. Dordrecht: Kluwer.MATH Bard, J. F. (1998). Practical bilevel optimization: Algorithms and applications. Dordrecht: Kluwer.MATH
48.
go back to reference Sinha, A., Malo, P., & Deb, K. (2018). A review on bilevel optimization: From classical to evolutionary approaches and applications. IEEE Transactions on Evolutionary Computation, 22(2), 276–295. Sinha, A., Malo, P., & Deb, K. (2018). A review on bilevel optimization: From classical to evolutionary approaches and applications. IEEE Transactions on Evolutionary Computation, 22(2), 276–295.
49.
go back to reference Cruz-Mejia, O., Marmolejo, J. A., & Vasant, P. (2018). Lead time performance in a internet product delivery supply chain with automatic consolidation. Journal of Ambient Intelligence and Humanized Computing, 9(3), 867–874. Cruz-Mejia, O., Marmolejo, J. A., & Vasant, P. (2018). Lead time performance in a internet product delivery supply chain with automatic consolidation. Journal of Ambient Intelligence and Humanized Computing, 9(3), 867–874.
50.
go back to reference Ibarra-Rojas, O. J., Delgado, F., Giesen, R., & Muñoz, J. C. (2015). Planning, operation, and control of bus transport systems: A literature review. Transportation Research Part B: Methodological, 77, 38–75. Ibarra-Rojas, O. J., Delgado, F., Giesen, R., & Muñoz, J. C. (2015). Planning, operation, and control of bus transport systems: A literature review. Transportation Research Part B: Methodological, 77, 38–75.
Metadata
Title
Approximating the Pareto front of a bi-objective problem in telecommunication networks using a co-evolutionary algorithm
Authors
José-Fernando Camacho-Vallejo
Cristóbal Garcia-Reyes
Publication date
15-12-2018
Publisher
Springer US
Published in
Wireless Networks / Issue 7/2020
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-018-01921-4

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