Solving the airline crew recovery problem by a genetic algorithm with local improvement

2005 ◽  
Vol 5 (2) ◽  
pp. 241-259 ◽  
Author(s):  
Yufeng Guo ◽  
Leena Suhl ◽  
Markus P. Thiel
Keyword(s):  
Genetic Algorithm ◽  
Airline Crew ◽  
Local Improvement ◽  
Crew Recovery ◽  
Recovery Problem

Airline Crew Recovery

2000 ◽  
Vol 34 (4) ◽  
pp. 337-348 ◽  
Author(s):  
Ladislav Lettovský ◽  
Ellis L. Johnson ◽  
George L. Nemhauser
Keyword(s):  
Airline Crew ◽  
Crew Recovery

scholarly journals An Enhanced Genetic Algorithm to Solve the Static and Multistage Transmission Network Expansion Planning

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Luis A. Gallego ◽  
Marcos J. Rider ◽  
Marina Lavorato ◽  
Antonio Paldilha-Feltrin
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Heuristic Algorithms ◽  
Initial Population ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Local Improvement ◽  
Linear Programming Problems

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem.

scholarly journals A Proposal of Genetic Algorithm with a Local Improvement Mechanism and Finding of Fuzzy Rules

1995 ◽  
Vol 7 (5) ◽  
pp. 978-987 ◽  
Author(s):  
Takeshi FURUHASHI ◽  
Ken NAKAOKA ◽  
Hiroshi MAEDA ◽  
Yoshiki UCHIKAWA
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Rules ◽  
Local Improvement

A Column Generation Approach to Railway Crew Recovery Problem in Disruption

2014 ◽  
Vol 134 (3) ◽  
pp. 418-424
Author(s):  
Jun Imaizumi ◽  
Rei Miura ◽  
Eiki Shigeta ◽  
Susumu Morito
Keyword(s):  
Column Generation ◽  
Crew Recovery ◽  
Recovery Problem
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