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Comparing evolutionary strategies on a biobjective cultural algorithm.

Carolina Lagos1, Broderick Crawford2, Enrique Cabrera3

  • 1Escuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, Chile.

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|September 26, 2014
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Summary
This summary is machine-generated.

Cultural algorithms (CAs) with different knowledge strategies were compared on the biobjective uncapacitated facility location problem (BOUFLP). The biobjective cultural algorithm (BOCA) using historical knowledge significantly improved performance over other evolutionary algorithms.

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Area of Science:

  • Computational Intelligence
  • Operations Research
  • Optimization

Background:

  • Evolutionary algorithms are effective for complex optimization.
  • Cultural algorithms (CAs) extend evolutionary algorithms using knowledge strategies.
  • Few studies explore evolutionary strategies' impact on biobjective uncapacitated facility location problems (BOUFLP).

Purpose of the Study:

  • To compare Cultural Algorithms (CAs) employing distinct evolutionary strategies: historical, circumstantial, and normative knowledge.
  • To evaluate these CAs on the biobjective uncapacitated facility location problem (BOUFLP).
  • To assess the performance impact of different evolutionary strategies within CAs for BOUFLP.

Main Methods:

  • Developed and applied three CAs with historical, circumstantial, and normative knowledge strategies.
  • Tested CAs on the biobjective uncapacitated facility location problem (BOUFLP).
  • Compared the proposed biobjective cultural algorithm (BOCA) against established algorithms like PAES and NSGA-II.
  • Utilized the hypervolume S metric for solution quality assessment.

Main Results:

  • The biobjective cultural algorithm (BOCA) incorporating historical knowledge demonstrated significant performance improvements.
  • BOCA outperformed other well-known evolutionary biobjective optimization algorithms.
  • The study highlights the crucial role of the evolutionary strategy in algorithm performance for BOUFLP.

Conclusions:

  • Cultural algorithms, particularly BOCA with historical knowledge, offer a promising approach for solving the BOUFLP.
  • The choice of evolutionary strategy significantly influences the effectiveness of CAs in biobjective optimization.
  • Further research can explore other knowledge strategies and problem variations.