AbstractA simple deterministic dynamic programming model is used as a general framework for the analysis of stochastic versions of three classical optimization problems: knapsack, traveling salesperson, and assembly line balancing problems. It is shown that this model can provide an alternative to the preference order models proposed for these problems. Counterexample to the optimality of the preference order models are presented
The use of stochastic orderings as a modeling tool has become standard in theory and applications of...
Finding optimal decisions often involves the consideration of certain random or unknown parameters. ...
We model an environment where orders arrive probabilistically over time, with their revenues and cap...
This paper deals with a problem o f dynamic optimization with values o f criteria function in the s...
AbstractA sequential decision model is developed in the context of which three principles of optimal...
This paper presents a model o f dynamic, discrete decision-making problem (finite number of periods...
Expected inventory order crossovers Occur if at the moment of ordering it is expected that orders wi...
Many problems that require decisions made over time can be formulated as dynamic linear programs. Co...
In this survey, we show that various stochastic optimization problems arising in option theory, in d...
Inventory control implies dynamic decision making. Therefore, dynamic programming seems an appropri...
Given two probability measures on sequential data, we investigate the transport problem with time-in...
Expected inventory order crossovers occur if at the moment of ordering it is expected that orders wi...
International audienceMany stochastic dynamic programming tasks in continuous action-spaces are tack...
Inventory control implies dynamic decision making. Therefore, dynamic programming seems an appropria...
For most order quantity/reorder point inventory systems, the stochastic model, which specifies the d...
The use of stochastic orderings as a modeling tool has become standard in theory and applications of...
Finding optimal decisions often involves the consideration of certain random or unknown parameters. ...
We model an environment where orders arrive probabilistically over time, with their revenues and cap...
This paper deals with a problem o f dynamic optimization with values o f criteria function in the s...
AbstractA sequential decision model is developed in the context of which three principles of optimal...
This paper presents a model o f dynamic, discrete decision-making problem (finite number of periods...
Expected inventory order crossovers Occur if at the moment of ordering it is expected that orders wi...
Many problems that require decisions made over time can be formulated as dynamic linear programs. Co...
In this survey, we show that various stochastic optimization problems arising in option theory, in d...
Inventory control implies dynamic decision making. Therefore, dynamic programming seems an appropri...
Given two probability measures on sequential data, we investigate the transport problem with time-in...
Expected inventory order crossovers occur if at the moment of ordering it is expected that orders wi...
International audienceMany stochastic dynamic programming tasks in continuous action-spaces are tack...
Inventory control implies dynamic decision making. Therefore, dynamic programming seems an appropria...
For most order quantity/reorder point inventory systems, the stochastic model, which specifies the d...
The use of stochastic orderings as a modeling tool has become standard in theory and applications of...
Finding optimal decisions often involves the consideration of certain random or unknown parameters. ...
We model an environment where orders arrive probabilistically over time, with their revenues and cap...