A computational method using genetic algorithms for obtaining Stackelberg solutions to two-level linear programming problems

2002 ◽  
Vol 85 (6) ◽  
pp. 55-62 ◽  
Author(s):  
Ichiro Nishizaki ◽  
Masatoshi Sakawa ◽  
Keiichi Niwa ◽  
Yasuhiro Kitaguchi
Keyword(s):  
Genetic Algorithms ◽  
Linear Programming ◽  
Computational Method ◽  
Stackelberg Solutions ◽  
Linear Programming Problems

Comparative Study of Different Optimization Algorithms Used for Obtaining Diesel-Biodiesel Blends

2019 ◽  
Vol 70 (6) ◽  
pp. 1893-1896
Author(s):  
Stefan Sandru ◽  
Ion Onutu
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithms ◽  
Linear Programming ◽  
Classical Method ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Biodiesel Blends ◽  
Dual Simplex ◽  
Linear Programming Problems

The purpose of this paper is to compare two different optimization methods, used in acquiring diesel-biodiesel blends. There were used five types of samples in order to enable the optimization of the final blend: there were chosen two types of hydrofined diesel fuel and there were synthesized three original types of biodiesel. The first optimization method used, dual simplex, is a classical method being used in solving linear programming problems. The second optimization method, the genetic algorithms, falls in the type of artificial intelligence algorithms, being an evolutionary method used when the problem requires searching an optimal solution in a great variety of valid solutions.

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