Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Modern heuristic techniques for combinatorial problems
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem
Journal of Global Optimization
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Bucket elimination for multiobjective optimization problems
Journal of Heuristics
Solving efficiently the 0-1 multi-objective knapsack problem
Computers and Operations Research
Speed-up techniques for solving large-scale biobjective TSP
Computers and Operations Research
An efficient implementation for the 0-1 multi-objective Knapsack problem
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
Two-phase Pareto local search for the biobjective traveling salesman problem
Journal of Heuristics
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
On beam search for multicriteria combinatorial optimization problems
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Computers and Operations Research
Algorithmic improvements on dynamic programming for the bi-objective {0,1} knapsack problem
Computational Optimization and Applications
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In this paper we introduce the concept of bound sets for multiobjective discrete optimization. We prove general results on lower and upper bound sets for combinatorial optimization problems with multiple objectives. We present general algorithms for constructing lower and upper bound sets for biobjective problems and provide numerical results on five different problem types.