In the present work, we are interested in the practical behavior of a new fptas to solve the approximation version of the 0-1 multi-objective knapsack problem. Nevertheless, our methodology focuses on very general techniques (such as dominance relations in dynamic programming) and thus may be applicable in the implementation of fptas for other problems as well. Extensive numerical experiments on various types of instances establish that our method performs very well both in terms of CPU time and size of solved instances. We point out some reasons for the good practical performance of our algorithm. A comparison with an exact method is also performed.ouinonouirechercheInternationa
International audienceThis paper presents several methodological and algorithmic improvements over a...
International audienceAn efficient parallel algorithm for the 0-1 knapsack problem is presented. The...
We consider the 0-1 Penalized Knapsack Problem (PKP). Each item has a profit, a weight and a penalty...
In the present work, we are interested in the practical behavior of a new fully polynomial time appr...
In the present work, we are interested in the practical behavior of a new fully polynomial time appr...
In this paper, we present an approach, based on dynamic programming, for solving 0-1 multi-objective...
In this paper, we present an approach, based on dynamic programming, for solving the 0–1 multi-objec...
∗ corresponding author In this paper, we present an approach, based on dynamic programming, for solv...
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
This paper presents several methodological and algorithmic improvements over a state-of-the-art dyna...
AbstractIn this paper, we present a dynamic programming (DP) algorithm for the multi-objective 0–1 k...
International audienceThis paper presents several methodological and algorithmic improvements over a...
International audienceAn efficient parallel algorithm for the 0-1 knapsack problem is presented. The...
We consider the 0-1 Penalized Knapsack Problem (PKP). Each item has a profit, a weight and a penalty...
In the present work, we are interested in the practical behavior of a new fully polynomial time appr...
In the present work, we are interested in the practical behavior of a new fully polynomial time appr...
In this paper, we present an approach, based on dynamic programming, for solving 0-1 multi-objective...
In this paper, we present an approach, based on dynamic programming, for solving the 0–1 multi-objec...
∗ corresponding author In this paper, we present an approach, based on dynamic programming, for solv...
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
International audienceThis paper presents a preprocessing procedure for the 0–1 multidimensional kna...
This paper presents several methodological and algorithmic improvements over a state-of-the-art dyna...
AbstractIn this paper, we present a dynamic programming (DP) algorithm for the multi-objective 0–1 k...
International audienceThis paper presents several methodological and algorithmic improvements over a...
International audienceAn efficient parallel algorithm for the 0-1 knapsack problem is presented. The...
We consider the 0-1 Penalized Knapsack Problem (PKP). Each item has a profit, a weight and a penalty...