Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem
Journal of Global Optimization
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Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Solving bicriteria 0-1 knapsack problems using a labeling algorithm
Computers and Operations Research
Multicriteria Optimization
Bound sets for biobjective combinatorial optimization problems
Computers and Operations Research
Solving efficiently the 0-1 multi-objective knapsack problem
Computers and Operations Research
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INFORMS Journal on Computing
An efficient implementation for the 0-1 multi-objective Knapsack problem
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
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KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
A two state reduction based dynamic programming algorithm for the bi-objective 0-1 knapsack problem
Computers & Mathematics with Applications
Computers & Mathematics with Applications
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This paper is devoted to a study of the impact of using bound sets in biobjective optimization. This notion, introduced by Villareal and Karwan [19], has been independently revisited by Ehrgott and Gandibleux [9], as well as by Sourd and Spanjaard [17]. The idea behind it is very general, and can therefore be adapted to a wide range of biobjective combinatorial problem. We focus here on the biobjective binary knapsack problem. We show that using bound sets in a two-phases approach [18] based on biobjective dynamic programming yields numerical results that outperform previous ones, both in execution times and memory requirements.