scholarly journals Cooperative Occupancy Decision Making of Multi-UAV in Beyond-Visual-Range Air Combat: A Game Theory Approach

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 11624-11634
Author(s):  
Yingying Ma ◽  
Guoqiang Wang ◽  
Xiaoxuan Hu ◽  
He Luo ◽  
Xing Lei
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Theory Approach ◽  
Air Combat ◽  
Visual Range ◽  
Multi Uav

Improving medical decision-making with a management science game theory approach to liver transplantation

Omega ◽  
2020 ◽  
Vol 94 ◽  
pp. 102050
Author(s):  
Francisco V. Mendonça ◽  
Margarida Catalão-Lopes ◽  
Rui Tato Marinho ◽  
José Rui Figueira
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Liver Transplantation ◽  
Medical Decision Making ◽  
Management Science ◽  
Medical Decision ◽  
Theory Approach

Multilevel Optimal Design of a Solar PV Array System Using Game Theory Approach

2019 ◽  
Author(s):  
Hoe-Gil Lee
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Optimal Design ◽  
System Level ◽  
Theory Approach ◽  
Solar Pv ◽  
Fixed Plate ◽  
Collector System ◽  
Cell Conversion ◽  
Conflicting Objectives

Abstract This study proposes a method, grounded in a multilevel decision-making approach, for a stationary fixed-plate photovoltaic (PV) collector system. The system is comprised of three different subsystems: cell, panel, and array. We consider photovoltaic effects for output performance and an inverter system for distribution from the PV collector, including multiple conflicting objectives in individual subsystems in terms of cell conversion efficiency, power output, incident solar energy, seasonal characteristics, and costs. In terms of the performance in individual subsystems, the problem is reformulated into several smaller subproblems at each subsystem, and a coordination problem at the system level is compromised for optimization purposes. Multilevel optimization for the stationary fixed-plate PV collector system is achieved through the results of single-objective optimization that uses Genetic Algorithm programming (GA) to find global optimum solutions with decision-making under modified game theory. Thus, this work contributes to the optimal design of a stationary fixed-plate PV collector system for the best compromise solution based on specified requirements.

scholarly journals Cooperative Attack-Defense Decision-Making of Multi-UAV Using Satisficing Decision-Enhanced Wolf Pack Search Algorithm

2021 ◽  
Author(s):  
Tongle Zhou ◽  
Mou Chen ◽  
Yuhui Wang ◽  
Ronggang Zhu ◽  
Chenguang Yang
Keyword(s):  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Decision Problem ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Target Information ◽  
Aerial Vehicles ◽  
Air Combat ◽  
Simulation Results ◽  
Multi Uav

Abstract Unmanned Aerial Vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack-defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack-defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. In order to improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making.

HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

2013 ◽  
Vol 04 (04) ◽  
pp. 1342004 ◽  
Author(s):  
HAIPENG KONG ◽  
NI LI
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Multiple Target ◽  
Quantum Bits ◽  
Quantum Genetic Algorithm ◽  
Air Combat ◽  
Modification Technique ◽  
Visual Range

In order to achieve the optimal attack outcome in the air combat under the beyond visual range (BVR) condition, the decision-making (DM) problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack (CMTA). In this paper, a heuristic quantum genetic algorithm (HQGA) is proposed to solve the DM problem. The originality of our work can be supported in the following aspects: (1) the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits (Q-bits); (2) the relative successful sequence probability (RSSP) is defined, based on which the priority attack vector is constructed; (3) the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper; (4) last but not the least, in some special conditions, the HQGA gets rid of the constraint described by other algorithms that to obtain a better result. In the end of this paper, two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.

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