Evolutionary algorithms for solving multi-objective travelling salesman problem

[1]  Derek C. Rose,et al.  Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[2]  Qingfu Zhang,et al.  Guidelines for developing effective Estimation of Distribution Algorithms in solving single machine scheduling problems , 2010, Expert Syst. Appl..

[3]  Taïcir Loukil,et al.  Multiple crossover genetic algorithm for the multiobjective traveling salesman problem , 2010, Electron. Notes Discret. Math..

[4]  Kay Chen Tan,et al.  Restricted Boltzmann machine based algorithm for multi-objective optimization , 2010, IEEE Congress on Evolutionary Computation.

[5]  Kay Chen Tan,et al.  An investigation on sampling technique for multi-objective restricted Boltzmann machine , 2010, IEEE Congress on Evolutionary Computation.

[6]  Thomas Stützle,et al.  The impact of design choices of multiobjective antcolony optimization algorithms on performance: an experimental study on the biobjective TSP , 2010, GECCO '10.

[7]  Zhen Ji,et al.  Towards a Memetic Feature Selection Paradigm [Application Notes] , 2010, IEEE Computational Intelligence Magazine.

[8]  Ferrante Neri,et al.  Memetic Compact Differential Evolution for Cartesian Robot Control , 2010, IEEE Computational Intelligence Magazine.

[9]  Yew-Soon Ong,et al.  Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[10]  Chuan-Kang Ting,et al.  Linkage Discovery through Data Mining [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[11]  Alessandro Sperduti,et al.  Mining Structured Data , 2010, IEEE Computational Intelligence Magazine.

[12]  Gen-Lang Chen,et al.  Solving Large-Scale TSP Using Adaptive Clustering Method , 2009, 2009 Second International Symposium on Computational Intelligence and Design.

[13]  Min Zhu,et al.  Solving TSP by using Lotka-Volterra neural networks , 2009, Neurocomputing.

[14]  Bassem Jarboui,et al.  An estimation of distribution algorithm for minimizing the total flowtime in permutation flowshop scheduling problems , 2009, Comput. Oper. Res..

[15]  Jun Xu,et al.  Ant Colony Optimization Based on Estimation of Distribution for the Traveling Salesman Problem , 2009, 2009 Fifth International Conference on Natural Computation.

[16]  Shi Lianshuan,et al.  An Improved Pareto Genetic Algorithm for Multi-objective TSP , 2009, 2009 Fifth International Conference on Natural Computation.

[17]  Xiaodong Li,et al.  Evolutionary algorithms and multi-objectivization for the travelling salesman problem , 2009, GECCO.

[18]  Jesús García,et al.  On the Model-Building Issue of Multi-Objective Estimation of Distribution Algorithms , 2009, HAIS.

[19]  Lu Lin,et al.  Maximum Entropy Estimation of Distribution Algorithm for JSSP under Uncertain Information Based on Rough Programming , 2009, 2009 International Workshop on Intelligent Systems and Applications.

[20]  Kay Chen Tan,et al.  A Competitive-Cooperative Coevolutionary Paradigm for Dynamic Multiobjective Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[21]  Qingfu Zhang,et al.  Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem , 2009 .

[22]  O. Yugay,et al.  Hybrid Genetic Algorithm for Solving Traveling Salesman Problem with Sorted Population , 2008, 2008 Third International Conference on Convergence and Hybrid Information Technology.

[23]  Tijmen Tieleman,et al.  Training restricted Boltzmann machines using approximations to the likelihood gradient , 2008, ICML '08.

[24]  Qingfu Zhang,et al.  This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 1 RM-MEDA: A Regularity Model-Based Multiobjective Estimation of , 2022 .

[25]  Mícheál Ó Foghlú,et al.  Frequent Closed Informative Itemset Mining , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[26]  Xiaoping Zhong,et al.  A Decision-Tree-Based Multi-objective Estimation of Distribution Algorithm , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[27]  Ming Yang,et al.  An Evolutionary Algorithm for Dynamic Multi-Objective TSP , 2007, ISICA.

[28]  Jia Yan,et al.  A Fast Evolutionary Algorithm for Traveling Salesman Problem , 2007, Third International Conference on Natural Computation (ICNC 2007).

[29]  Qingfu Zhang,et al.  An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem , 2007, GECCO '07.

[30]  Francisco Herrera,et al.  A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP , 2007, Eur. J. Oper. Res..

[31]  Geoffrey E. Hinton,et al.  Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.

[32]  Kay Chen Tan,et al.  Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation , 2007, Eur. J. Oper. Res..

[33]  Moustapha Diaby,et al.  The traveling salesman problem: A Linear programming formulation of , 2006, ArXiv.

[34]  Chelliah Sriskandarajah,et al.  A review of TSP based approaches for flowshop scheduling , 2006, Eur. J. Oper. Res..

[35]  Carlos A. Coello Coello,et al.  Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Comput. Intell. Mag..

[36]  J. A. Lozano,et al.  Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing) , 2006 .

[37]  David E. Goldberg,et al.  Limits of scalability of multiobjective estimation of distribution algorithms , 2005, 2005 IEEE Congress on Evolutionary Computation.

[38]  Geoffrey E. Hinton.  What kind of graphical model is the brain? , 2005, IJCAI.

[39]  Carlos A. Coello Coello,et al.  A proposal to use stripes to maintain diversity in a multi-objective particle swarm optimizer , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[40]  Byoung-Tak Zhang,et al.  Multiobjective evolutionary optimization of DNA sequences for reliable DNA computing , 2005, IEEE Transactions on Evolutionary Computation.

[41]  David E. Goldberg,et al.  Multiobjective hBOA, clustering, and scalability , 2005, GECCO '05.

[42]  Oscar Cordón,et al.  An Empirical Analysis of Multiple Objective Ant Colony Optimization Algorithms for the Bi-criteria TSP , 2004, ANTS Workshop.

[43]  Bernhard Sendhoff,et al.  Voronoi-based estimation of distribution algorithm for multi-objective optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[44]  Edmondo A. Minisci,et al.  MOPED: A Multi-objective Parzen-Based Estimation of Distribution Algorithm for Continuous Problems , 2003, EMO.

[45]  Dirk Thierens,et al.  Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms , 2002, Int. J. Approx. Reason..

[46]  Marco Laumanns,et al.  Bayesian Optimization Algorithms for Multi-objective Optimization , 2002, PPSN.

[47]  Jacek Blazewicz,et al.  Hybrid Genetic Algorithm for DNA Sequencing with Errors , 2002, J. Heuristics.

[48]  Geoffrey E. Hinton.  Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.

[49]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[50]  J. A. Lozano,et al.  Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .

[51]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[52]  Eckart Zitzler,et al.  Evolutionary algorithms for multiobjective optimization: methods and applications , 1999 .

[53]  Heinz Mühlenbein,et al.  The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.

[54]  H. Mühlenbein,et al.  From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.

[55]  David E. Goldberg,et al.  Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise , 1996, Evolutionary Computation.

[56]  Chryssi Malandraki,et al.  A restricted dynamic programming heuristic algorithm for the time dependent traveling salesman problem , 1996 .

[57]  Mark A. Wellman,et al.  A genetic algorithm approach to optimization of asynchronous automatic assembly systems , 1995 .

[58]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[59]  G. Laporte.  The traveling salesman problem: An overview of exact and approximate algorithms , 1992 .

[60]  Gerhard Reinelt,et al.  Fast Heuristics for Large Geometric Traveling Salesman Problems , 1992, INFORMS J. Comput..

[61]  Gilbert Laporte,et al.  A Combinatorial Optimization Problem Arising in Dartboard Design , 1991 .

[62]  E. Aarts,et al.  Boltzmann machines for travelling salesman problems , 1989 .

[63]  Giovanni Rinaldi,et al.  Branch-and-cut approach to a variant of the traveling salesman problem , 1988 .

[64]  Kay Chen Tan,et al.  Multi-objective and prioritized berth allocation in container ports , 2010, Ann. Oper. Res..

[65]  Zhou Xin.  Meliorative tabu search algorithm for TSP problem , 2008 .

[66]  Xu Ning,et al.  Simulated Annealing Algorithm Based on Controllable Temperature for Solving TSP , 2007 .

[67]  Pedro Larrañaga,et al.  Towards a New Evolutionary Computation - Advances in the Estimation of Distribution Algorithms , 2006, Towards a New Evolutionary Computation.

[68]  David E. Goldberg,et al.  Multiobjective Estimation of Distribution Algorithms , 2006, Scalable Optimization via Probabilistic Modeling.

[69]  María Cristina González Morgado.  Contributions on theoretical aspects of estimation of distributions algorithms , 2006 .

[70]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[71]  Fernando G. Lobo,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).