Solution algorithm for an optimistic linear Stackelberg problem

2014 ◽  
Vol 41 ◽  
pp. 277-281 ◽  
Author(s):  
Stephan Dempe ◽  
Susanne Franke
Keyword(s):  
Solution Algorithm ◽  
Stackelberg Problem

Solution Algorithm

THERMOPEDIA ◽  
2008 ◽  
Author(s):  
Pedro J. Coelho
Keyword(s):  
Solution Algorithm

Pseudo-updated constrained solution algorithm for nonlinear heat conduction

AIAA Journal ◽  
1983 ◽  
Vol 21 (6) ◽  
pp. 902-908 ◽  
Author(s):  
Surapong Tovichakchaikul ◽  
Joseph Padovan
Keyword(s):  
Heat Conduction ◽  
Solution Algorithm ◽  
Nonlinear Heat Conduction

Discrete Dynamic Shortest Path Problems in Transportation Applications: Complexity and Algorithms with Optimal Run Time

1998 ◽  
Vol 1645 (1) ◽  
pp. 170-175 ◽  
Author(s):  
Ismail Chabini
Keyword(s):  
Large Scale ◽  
Shortest Paths ◽  
Transportation Systems ◽  
Solution Algorithm ◽  
Shortest Path Problems ◽  
Discrete Dynamic ◽  
Solution Algorithms ◽  
Dynamic Network Models ◽  
Early Results ◽  
Run Time

A solution is provided for what appears to be a 30-year-old problem dealing with the discovery of the most efficient algorithms possible to compute all-to-one shortest paths in discrete dynamic networks. This problem lies at the heart of efficient solution approaches to dynamic network models that arise in dynamic transportation systems, such as intelligent transportation systems (ITS) applications. The all-to-one dynamic shortest paths problem and the one-to-all fastest paths problems are studied. Early results are revisited and new properties are established. The complexity of these problems is established, and solution algorithms optimal for run time are developed. A new and simple solution algorithm is proposed for all-to-one, all departure time intervals, shortest paths problems. It is proved, theoretically, that the new solution algorithm has an optimal run time complexity that equals the complexity of the problem. Computer implementations and experimental evaluations of various solution algorithms support the theoretical findings and demonstrate the efficiency of the proposed solution algorithm. The findings should be of major benefit to research and development activities in the field of dynamic management, in particular real-time management, and to control of large-scale ITSs.

Underground Gas Storage Inventory Analysis by a Noniterative Method

2004 ◽  
Vol 127 (2) ◽  
pp. 163-165 ◽  
Author(s):  
Ning Liu ◽  
Faruk Civan
Keyword(s):  
Production Rate ◽  
Gas Storage ◽  
Solution Algorithm ◽  
System Model ◽  
Inventory Analysis ◽  
Underground Gas Storage ◽  
Temperature Conditions ◽  
Practical Model ◽  
Variable Production

Underground gas storage inventory and conditions are predicted using a practical model and a noniterative solution algorithm. Various simulation scenarios concerning underground gas storage in depleted reservoirs with variable production rate and temperature conditions demonstrate the effectiveness of this approach. It is shown that the gas storage parameters can be determined conveniently by solving the system model directly without resorting to the tedious procedures of the previous approaches.

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