Binary fish migration optimization for solving unit commitment

Jeng-Shyang Pan, Pei Hu, Shu-Chuan Chu

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Inspired by migratory graying, Pan et al. proposed the fish migration optimization (FMO) algorithm. It integrates the models of migration and swim into the optimization process. This paper firstly proposes a binary version of FMO, called BFMO. In order to improve the search ability of BFMO, ABFMO is introduced to solve the problems of stagnation and falling into local traps. The transfer function is responsible for mapping the continuous search space to the binary space. It plays a critical factor in the binary meta-heuristics. This paper brings a new transfer function and compares it with the transfer functions used by BPSO, BGSA and BGWO. Experiments prove that the new transfer function has realized good results in the solving quality. Unit commitment (UC) is a NP-hard binary optimization problem. BFMO and ABFMO are tested with the IEEE benchmark systems consisting of various generating units with 24-h demand horizon. The effectivenesses of BFMO and ABFMO are compared with seven binary evolutionary algorithms. The simulation results and non-parametric tests verify that they achieve great performance.

Original languageEnglish
Article number120329
Number of pages11
JournalENERGY
Volume226
DOIs
Publication statusPublished - 1 Jul 2021

Keywords

  • Binary
  • Fish Migration Optimization
  • Optimization
  • Transfer function
  • Unit commitment

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