An Adaptive Quantum-based Evolutionary Algorithm for Multiobjective Optimization
نویسنده
چکیده
An Adaptive Quantum-based Multi-criterion Evolutionary Algorithm called AQMEA is a new paradigm of decision making for complex systems. Quantum-based algorithms utilize a new representation for the smallest unit of information, called a Q-bit, for the probabilistic representation that is based on the concept of qubits. Evolutionary computing with Q-bit chromosomes has a better characteristic of population diversity than other representations, since it can represent linear superposition of states probabilistically. Moreover, we consider the three-criterion problem of task assignment. Key-Words: Quantum algorithms, multi-criterion optimization, distributed systems
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