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Related Experiment Video

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Novel metaheuristic based on multiverse theory for optimization problems in emerging systems.

Eghbal Hosseini1, Kayhan Zrar Ghafoor2,3, Ali Emrouznejad4

  • 1Mechanical and Energy Engineering Department, Erbil Technical Engineering College, Erbil Polytechnic University, Kurdistan Region, Iraq.

Applied Intelligence (Dordrecht, Netherlands)
|November 12, 2021
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Summary
This summary is machine-generated.

A new Multiverse Algorithm (MVA) optimizes cyber-physical systems (CPS) by mimicking multiverse principles. This meta-heuristic approach enhances efficiency and robustness for complex optimization problems.

Keywords:
Bi-level optimizationConstrained optimizationMeta-heuristicsMultiverse algorithm (MVA)

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Area of Science:

  • Computer Science
  • Optimization Theory
  • Cyber-Physical Systems

Background:

  • Optimizing cyber-physical systems (CPS) for efficiency and robustness is a critical challenge.
  • Meta-heuristic algorithms offer promising solutions for complex optimization tasks in CPS.

Purpose of the Study:

  • To introduce a novel meta-heuristic algorithm, the Multiverse Algorithm (MVA), inspired by Multiverse Theory.
  • To address NP-hard optimization problems, including non-linear and multi-level programming, within CPS.

Main Methods:

  • The MVA algorithm generates new populations by closely following initial solutions, mirroring parallel universes.
  • It distributes solutions across the feasible region, inspired by the Big Bang.
  • The algorithm's effectiveness is evaluated on a suite of test problems.

Main Results:

  • The MVA algorithm demonstrated superior performance compared to existing state-of-the-art methods.
  • It effectively solved optimization problems with large feasible regions.
  • Key metrics included solution feasibility, efficiency, and convergence speed (number of iterations).

Conclusions:

  • The proposed Multiverse Algorithm (MVA) is a highly effective meta-heuristic for solving complex optimization problems in CPS.
  • MVA shows significant potential for improving the efficiency and robustness of cyber-physical systems.