A new idea for addressing multi-objective combinatorial optimization: Quantum multi-agent evolutionary algorithms

机译：解决多目标组合优化的新思路：量子多智能体进化算法

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Multi-objective combinatorial optimization (MOCO) problem is investigated in this paper. Combining the characters of agent and quantum-bit, a new idea, i.e., Quantum multi-agent evolutionary algorithms (QMAEA), for addressing MOCO problem is proposed. In QMAEA, each agent represented with quantum-bit is defined as a solution. Several operations such as evaluation-operation, competition-operation, mutation-operation, and local-evolution-Operation are introduced in QMAEA. The working flow of QMAEA is presented.

机译：研究了多目标组合优化（MOCO）问题。结合智能体和量子位的特点，提出了一种解决MOCO问题的新思路，即量子多智能体进化算法（QMAEA）。在QMAEA中，将用量子位表示的每个代理定义为一个解决方案。 QMAEA中引入了一些操作，例如评估操作，竞争操作，变异操作和局部进化操作。介绍了QMAEA的工作流程。

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《Information Sciences and Systems, 2009. CISS 2009》|2009年|28-31|共4页
会议地点 Baltimore MD(US);Baltimore MD(US);Baltimore MD(US)
作者
Dongming Zhao; Fei Tao;
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Dept. of Electr. Comput. Eng., Univ. of Michigan, Dearborn, MI;

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combinatorial mathematics; evolutionary computation; competition-operation; evaluation-operation; local-evolution-operation; multi-objective combinatorial optimization; mutation-operation; quantum multi-agent evolutionary algorithms; quantum-bit; Quantum; agent; multi-objective combinatorial optimization (MOCO);

机译：组合数学;进化计算;竞争操作;评估操作;局部演化操作;多目标组合优化;变异操作;量子多智能体演化算法;量子位;量子;智能体;多目标组合优化（MOCO）;

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专利

1. QMAEA: A quantum multi-agent evolutionary algorithm for multi-objective combinatorial optimization [J] . F Tao, YJ Laili, L Zhang, Simulation . 2014,第2期

机译：QMAEA：用于多目标组合优化的量子多智能体进化算法
2. Evolutionary Algorithm based on the Automata Theory for the Multi-objective Optimization of Combinatorial Problems [J] . Elias D. Ni?o-Ruiz International journal of computers, communications and control . 2014,第5期

机译：基于自动机理论的组合问题多目标优化进化算法
3. Evolutionary Algorithm based on the Automata Theory for the Multi-objective Optimization of Combinatorial Problems [J] . Elias D. Ni?o-Ruiz IAENG Internaitonal journal of computer science . 2014,第5期

机译：基于自动机理论的组合问题多目标优化进化算法
4. A new idea for addressing multi-objective combinatorial optimization: Quantum multi-agent evolutionary algorithms [C] . Dongming Zhao, Fei Tao Annual Conference on Information Sciences and Systems . 2009

机译：解决多目标组合优化的新思路：量子多功能进化算法
5. Evolutionary Game Theoretic Multi-Objective Optimization Algorithms and Their Applications. [D] . Ren Cheng, Yi. 2017

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6. Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms [O] . Haigen Hu, Lihong Xu, Ruihua Wei, 2011

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7. Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization [O] . Leonardo C. T. Bezerra, Manuel López-Ibáñez, Thomas Stützle 2014

机译：多目标组合优化的进化算法自动设计

A new idea for addressing multi-objective combinatorial optimization: Quantum multi-agent evolutionary algorithms

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