Add to ORKGMost optimization problems in real life do not have accurate estimates of the problem parameters at the optimization phase. Stochastic optimization and robust optimization are two approaches mostl
We consider a generalization of the 0–1 knapsack problem in which the profit of each item can take a...
Minmax regret optimization aims at finding robust solutions that perform best in the worst-case, com...
The Binary Integer Programming problem (BIP) is a mathematical optimization problem, with linear obj...
Many real life optimization problems do not have accurate estimates of the problem parameters at the...
Many real life optimization problems do not have accurate estimates of the problem parameters at the...
We consider the generalized assignment problem (GAP) with min-max regret criterion under interval co...
This paper investigates the complexity of the min–max and min–max regret assignment problems both in...
AbstractWe consider combinatorial optimization problems with uncertain parameters of the objective f...
Many combinatorial optimization problems arising in real-world applications do not have accurate est...
International audienceIn this paper, we provide a generic anytime lower bounding procedure for minma...
In optimization, it is used to deal with uncertain and inaccurate factors which make difficult the a...
In this chapter a class of scheduling problems with uncertain parameters is dis-cussed. The uncertai...
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have bee...
International audienceThe following optimization problem is studied. There are several sets of integ...
In this paper, we propose a probabilistic model for minimizing the anticipated regret in com-binator...
We consider a generalization of the 0–1 knapsack problem in which the profit of each item can take a...
Minmax regret optimization aims at finding robust solutions that perform best in the worst-case, com...
The Binary Integer Programming problem (BIP) is a mathematical optimization problem, with linear obj...
Many real life optimization problems do not have accurate estimates of the problem parameters at the...
Many real life optimization problems do not have accurate estimates of the problem parameters at the...
We consider the generalized assignment problem (GAP) with min-max regret criterion under interval co...
This paper investigates the complexity of the min–max and min–max regret assignment problems both in...
AbstractWe consider combinatorial optimization problems with uncertain parameters of the objective f...
Many combinatorial optimization problems arising in real-world applications do not have accurate est...
International audienceIn this paper, we provide a generic anytime lower bounding procedure for minma...
In optimization, it is used to deal with uncertain and inaccurate factors which make difficult the a...
In this chapter a class of scheduling problems with uncertain parameters is dis-cussed. The uncertai...
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have bee...
International audienceThe following optimization problem is studied. There are several sets of integ...
In this paper, we propose a probabilistic model for minimizing the anticipated regret in com-binator...
We consider a generalization of the 0–1 knapsack problem in which the profit of each item can take a...
Minmax regret optimization aims at finding robust solutions that perform best in the worst-case, com...
The Binary Integer Programming problem (BIP) is a mathematical optimization problem, with linear obj...