Entry optimization using mixed integer linear programming
Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committ...
Ausführliche Beschreibung
Autor*in: |
Baek, Seungmin [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2016 |
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© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 |
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Enthalten in: International Journal of Control, Automation and Systems - Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009, 14(2016), 1 vom: Feb., Seite 282-290 |
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Übergeordnetes Werk: |
volume:14 ; year:2016 ; number:1 ; month:02 ; pages:282-290 |
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DOI / URN: |
10.1007/s12555-014-0270-6 |
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10.1007/s12555-014-0270-6 doi (DE-627)SPR02641287X (SPR)s12555-014-0270-6-e DE-627 ger DE-627 rakwb eng Baek, Seungmin verfasserin aut Entry optimization using mixed integer linear programming 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. Decision making (dpeaa)DE-He213 game theory (dpeaa)DE-He213 military operation (dpeaa)DE-He213 MILP (mixed integer linear programming) (dpeaa)DE-He213 resource allocation (dpeaa)DE-He213 Moon, Sungwon aut Kim, H. Jin aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 14(2016), 1 vom: Feb., Seite 282-290 (DE-627)SPR026303256 nnns volume:14 year:2016 number:1 month:02 pages:282-290 https://dx.doi.org/10.1007/s12555-014-0270-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 14 2016 1 02 282-290 |
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10.1007/s12555-014-0270-6 doi (DE-627)SPR02641287X (SPR)s12555-014-0270-6-e DE-627 ger DE-627 rakwb eng Baek, Seungmin verfasserin aut Entry optimization using mixed integer linear programming 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. Decision making (dpeaa)DE-He213 game theory (dpeaa)DE-He213 military operation (dpeaa)DE-He213 MILP (mixed integer linear programming) (dpeaa)DE-He213 resource allocation (dpeaa)DE-He213 Moon, Sungwon aut Kim, H. Jin aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 14(2016), 1 vom: Feb., Seite 282-290 (DE-627)SPR026303256 nnns volume:14 year:2016 number:1 month:02 pages:282-290 https://dx.doi.org/10.1007/s12555-014-0270-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 14 2016 1 02 282-290 |
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10.1007/s12555-014-0270-6 doi (DE-627)SPR02641287X (SPR)s12555-014-0270-6-e DE-627 ger DE-627 rakwb eng Baek, Seungmin verfasserin aut Entry optimization using mixed integer linear programming 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. Decision making (dpeaa)DE-He213 game theory (dpeaa)DE-He213 military operation (dpeaa)DE-He213 MILP (mixed integer linear programming) (dpeaa)DE-He213 resource allocation (dpeaa)DE-He213 Moon, Sungwon aut Kim, H. Jin aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 14(2016), 1 vom: Feb., Seite 282-290 (DE-627)SPR026303256 nnns volume:14 year:2016 number:1 month:02 pages:282-290 https://dx.doi.org/10.1007/s12555-014-0270-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 14 2016 1 02 282-290 |
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Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 |
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Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 |
abstract_unstemmed |
Abstract An appropriate selection of agents to participate in a confrontation such as a game or combat depends on the types of the opposing team. This paper investigates the problem of determining a combination of agents to fight in a combat between two forces. When the types of enemy agents committed to the combat are not known, game theory provides the best response to the opponent. The entry game is solved by using mixed integer linear programming (MILP) to consider the constraints on resources in a game theoretic approach. Simulations for the examples involving three different sets of military forces are performed using an optimization tool, which demonstrates that the optimal entry is properly selected corresponding to the opposing force. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016 |
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Entry optimization using mixed integer linear programming |
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https://dx.doi.org/10.1007/s12555-014-0270-6 |
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Moon, Sungwon Kim, H. Jin |
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