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Nature and Quantum-Inspired Procedures - A Short Literature Review.

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Quantum-inspired metaheuristics offer innovative approaches and superior results. This review covers their development and application on current quantum computers.

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Area of Science:

  • Computer Science
  • Quantum Computing
  • Artificial Intelligence

Background:

  • Quantum-inspired algorithms predate public awareness of quantum computers.
  • These algorithms have established a strong reputation for innovation and performance.
  • The field has seen significant advancements over nearly two decades.

Purpose of the Study:

  • To provide a comprehensive review of quantum-inspired metaheuristics.
  • To focus on algorithms applicable to existing quantum computing hardware.
  • To summarize the current state of research and development.

Main Methods:

  • Review of existing literature on quantum-inspired metaheuristics.
  • Analysis of algorithm characteristics and performance metrics.
  • Identification of algorithms suitable for current quantum hardware.

Main Results:

  • Quantum-inspired metaheuristics combine novel features with enhanced results.
  • A substantial body of research exists, demonstrating diverse applications.
  • Specific algorithms are highlighted for their compatibility with present quantum systems.

Conclusions:

  • Quantum-inspired metaheuristics represent a mature and effective field.
  • These algorithms offer practical advantages for current quantum computing platforms.
  • Continued research promises further advancements in optimization and problem-solving.