Multi-objective Optimization for Common and Special Components: First Step Toward Network Optimization of Regular and Non-Regular Flights

Takahiro Jinba (), Hiroto Kitagawa (), Eriko Azuma (), Keiji Sato (), Hiroyuki Sato (), Kiyohiko Hattori () and Keiki Takadama ()
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Takahiro Jinba: Graduated School of Informatics and Engineering, The University of Electro-Communications, Chofu 182-8585, Japan
Hiroto Kitagawa: The University of Electro-Communications, Chofu 182-8585, Japan
Eriko Azuma: The University of Electro-Communications, Chofu 182-8585, Japan
Keiji Sato: The University of Electro-Communications, Chofu 182-8585, Japan
Hiroyuki Sato: The University of Electro-Communications, Chofu 182-8585, Japan
Kiyohiko Hattori: The University of Electro-Communications, Chofu 182-8585, Japan
Keiki Takadama: The University of Electro-Communications, Chofu 182-8585, Japan

New Mathematics and Natural Computation (NMNC), 2015, vol. 11, issue 02, 183-199

Abstract: To optimize the problem composed of (i) the common components which should be optimized from the viewpoint of all objective functions and (ii) the special components which should be optimized from the viewpoint of one of the objective functions, this paper proposes a new multi-objective optimization method which optimizes not only the common components for all objective functions but also the special ones for each objective function. To investigate the effectiveness of the proposed method, this paper tested our method on the test-bed problem which is an extended version of the 0/1 knapsack problem. The intensive experiments have revealed the following implications: (i) Our method finds better solutions which have higher fitness than the conventional method (NSGA-II); (ii) our method can find the solutions that had a large norm (which corresponds to a high profit of an airline company in the flight scheduling problem) with the high rate of the common components; and (iii) since the crowding distance employed in our method contributes to keeping the diversity during the solution search, our method has high exploration capability of solutions.

Keywords: Multi-objective optimization; common and special components optimization; evolutionary algorithm; 0/1 knapsack problem (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1142/S1793005715400050

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