On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem
Journal of Global Optimization
Solving bicriteria 0-1 knapsack problems using a labeling algorithm
Computers and Operations Research
Approximating Multiobjective Knapsack Problems
Management Science
Multicriteria Optimization
Bound sets for biobjective combinatorial optimization problems
Computers and Operations Research
On embedding subclasses of height-balanced trees in hypercubes
Information Sciences: an International Journal
Labeling algorithms for multiple objective integer knapsack problems
Computers and Operations Research
Dynamic programming with ordered structures: Theory, examples and applications
Fuzzy Sets and Systems
Greedy algorithms for a class of knapsack problems with binary weights
Computers and Operations Research
A two state reduction based dynamic programming algorithm for the bi-objective 0-1 knapsack problem
Computers & Mathematics with Applications
A strategy-oriented operation module for recommender systems in E-commerce
Computers and Operations Research
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
Computers & Mathematics with Applications
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
Multicriteria 0-1 knapsack problems with k-min objectives
Computers and Operations Research
Algorithmic improvements on dynamic programming for the bi-objective {0,1} knapsack problem
Computational Optimization and Applications
A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming
Applied Soft Computing
Interactive procedure for a multiobjective stochastic discrete dynamic problem
Journal of Global Optimization
Hi-index | 0.01 |
In this paper, we present an approach, based on dynamic programming, for solving the 0-1 multi-objective knapsack problem. The main idea of the approach relies on the use of several complementary dominance relations to discard partial solutions that cannot lead to new non-dominated criterion vectors. This way, we obtain an efficient method that outperforms the existing methods both in terms of CPU time and size of solved instances. Extensive numerical experiments on various types of instances are reported. A comparison with other exact methods is also performed. In addition, for the first time to our knowledge, we present experiments in the three-objective case.