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Memetic Salp Swarm Algorithm for economic load dispatch problems.

Mohammed A Awadallah1,2, Mohammed Azmi Al-Betar3,4, Malik Braik5

  • 1Department of Computer Science, Al-Aqsa University, P.O. Box 4051, Gaza, Palestine.

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|August 20, 2025
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Summary
This summary is machine-generated.

This study introduces a novel hybrid Salp Swarm Algorithm (SSA) for Economic Load Dispatch (ELD) problems, enhancing optimization efficiency for complex power systems. The new method, MSSA, effectively handles severe constraints, demonstrating superior performance in various generator unit scenarios.

Keywords:
Adaptive β-hill climbing optimizerEconomic load dispatchMemetic techniquesOptimizationSalp swarm algorithm

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Area of Science:

  • Electrical Engineering
  • Computational Intelligence
  • Optimization Algorithms

Background:

  • Economic Load Dispatch (ELD) is a critical optimization problem in electrical engineering.
  • Traditional methods struggle with the non-convex, multi-modal, and severely constrained nature of ELD.
  • Existing algorithms often fall short in efficiently solving complex ELD scenarios.

Purpose of the Study:

  • To present a hybrid Salp Swarm Algorithm (SSA) integrated with Adaptive β-hill climbing optimizer (AβHCO) for solving Economic Load Dispatch (ELD) problems.
  • To introduce a novel memetic algorithm (MSSA) that combines global search (SSA) and local refinement (AβHCO) for enhanced optimization.
  • To evaluate the performance of the proposed MSSA algorithm on various ELD problem instances with different constraint sets.

Main Methods:

  • Hybridization of Salp Swarm Algorithm (SSA) with Adaptive β-hill climbing optimizer (AβHCO) to create a memetic algorithm (MSSA).
  • SSA acts as a general refinement agent (gene encoding), while AβHCO provides local refinement (meme).
  • Testing MSSA on diverse ELD problems, including those with load balance, output, restricted operating zones, and ramp rate limit constraints, across multiple generator unit configurations (3UG-850 MW to 80UG-21000 MW).

Main Results:

  • The proposed MSSA algorithm demonstrated significant feasibility and usefulness in solving complex ELD problems.
  • Comparative results indicate that MSSA outperforms existing algorithms in handling severe constraints.
  • MSSA effectively addressed various ELD scenarios, from small to large-scale generator systems.

Conclusions:

  • The hybrid MSSA algorithm offers a robust and efficient solution for Economic Load Dispatch problems.
  • The memetic approach combining global and local search effectively tackles the challenges of non-convexity and severe constraints in ELD.
  • MSSA shows promise for practical application in power system optimization.