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In this article we present a generalization of Markov Decision Processes with discreet time where the immediate rewards in every period are not deterministic but random, with the two first moments of the distribution given.Formulas are developed to calculate the expected value and the variance of the reward of the process, formulas which generalize and partially correct other results. We make some observations about the distribution of rewards for processes with limited or unlimited horizon and...
    			                    
    			                 
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    			                    
                                       
We consider two parallel M/M/1 queues. The server at one of the queues
is subject to intermittent breakdowns. By the theory of dynamic 
programming, we determine a threshold optimal policy which consists 
to transfer, when it is necessary, the customers that arrive at the first 
queue towards the second queue in order to minimize an instantaneous cost
depending of the two queue lengths.
    			                    
    			                 
    		                
    		                
    		            
    			    
    		            
    		                
    		                
    		                
    			                
    			                    
                                       
El QAP-Arbol es un caso especial del problema de asignación cuadrática en que los flujos distintos de cero forman un árbol. No se requiere ninguna condición para la matriz de distancias. En este artículo presentamos una formulación del QAP-Arbol como un problema de programación lineal entera. Basándonos en esta formulación hemos construido cuatro relajaciones lagrangianas distintas que nos permiten obtener una serie de cotas inferiores para este problema. Para resolver una de estas relajaciones,...
    			                    
    			                 
    		                
    		                
    		            
    			    			
    			 
 
    			
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