Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Bi-Criterion Optimization with Multi Colony Ant Algorithms
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Approximating the Pareto curve with local search for the bicriteria TSP(1,2) problem
Theoretical Computer Science
Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
A new MOEA for multi-objective TSP and Its convergence property analysis
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
A two-phase local search for the biobjective traveling salesman problem
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
A Novel Weight Design in Multi-objective Evolutionary Algorithm
CIS '10 Proceedings of the 2010 International Conference on Computational Intelligence and Security
Hype: An algorithm for fast hypervolume-based many-objective optimization
Evolutionary Computation
An adaptive evolutionary multi-objective approach based on simulated annealing
Evolutionary Computation
A hybrid heuristic for the traveling salesman problem
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
IEEE Transactions on Evolutionary Computation
RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm
IEEE Transactions on Evolutionary Computation
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The traveling salesman problem (TSP) is a well known NP-hard benchmark problem for discrete optimization. However, there is a lack of TSP test instances for multiobjective optimization and some current TSP instances are combined to form a multiobjective TSP (MOTSP). In this paper, we present a way to systematically design MOTSP instances based on current TSP test instances, of which the degree of conflict between the objectives is measurable. Furthermore, we propose an approach, named multiobjective estimation of distribution algorithm based on decomposition (MEDA/D), which utilizes decomposition based techniques and probabilistic model based methods, to tackle the newly designed MOTSP test suite. In MEDA/D, an MOTSP is decomposed into a set of scalar objective sub-problems and a probabilistic model, using both priori and learned information, is built to guide the search for each sub-problem. By the cooperation of neighbor sub-problems, MEDA/D could optimize all the sub-problems simultaneously and thus find an approximation to the original MOTSP in a single run. The experimental results show that MEDA/D outperforms MOACO and MOEA/D-ACO, two ant colony based methods, on most of the given test instances and MEDA/D is insensible to its control parameters.