Minimization of Testing Costs in Capacity-Constrained Database Migration

Author(s):  
K. Subramani ◽  
Bugra Caskurlu ◽  
Alvaro Velasquez
2020 ◽  
Vol 46 (6) ◽  
pp. 365-368
Author(s):  
William B. Weeks ◽  
Jason Pike ◽  
Christopher J. Schaeffer ◽  
Mathew J. Devine ◽  
John M. Ventura ◽  
...  

1978 ◽  
Vol 92 (3) ◽  
pp. 387 ◽  
Author(s):  
Robert E. Dansby

2001 ◽  
Vol 31 (2) ◽  
pp. 236-245 ◽  
Author(s):  
A Maarit I Kallio

Efficient functioning of the wood market is crucial in a country where the forest sector is of strong macroeconomic importance. We investigate the possibility of noncompetitive behavior of the buyers in the Finnish pulpwood market. We simulate the buyers' behavior under alternative competition structures (perfect competition, Cournot oligopsony, and monopsony) and compare the simulated equilibria with the observed behavior in the years 1988–1997. In the static models the pulp industry firms are assumed to maximize their short-run variable profits either under fixed production capacity or, hypothetically, under variable capacity. The results suggest that, during the boom years, the industry has been capacity constrained, sometimes even for monopsony output. During the recession years, the actual wood prices have often been between simulated Cournot oligopsony and monopsony prices. Hence, noncompetitive behavior of the buyers is possible during the recessions. The capacity investment behavior of the industry is explored with dynamic models. The conclusions from these models depend on the price elasticity of pulpwood supply used.


Author(s):  
Jianfang Yang ◽  
Hao Lin ◽  
Junbiao Guan

In many public spaces (e.g. colleges and shopping malls), people are frequently distributed discretely, and thus, single-source evacuation, which means there’s only one point of origin, is not always a feasible solution. Hence, this paper discusses a multi-source evacuation model and algorithm, which are intended to evacuate all the people that are trapped within the minimum possible time. This study presents a fast flow algorithm to prioritize the most time-consuming source point under the constraint of route and exit capacity to reduce the evacuation time. This fast flow algorithm overcomes the deficiencies in the existing global optimization fast flow algorithm and capacity constrained route planner (CCRP) algorithm. For the fast flow algorithm, the first step is to determine the optimal solution to single-source evacuation and use the evacuation time of the most time-consuming source and exit gate set as the initial solution. The second step is to determine a multi-source evacuation solution by updating the lower limit of the current evacuation time and the exit gate set continually. The final step is to verify the effectiveness and feasibility of the algorithm through comparison.


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