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Putting Continuous Metaheuristics to Work in Binary Search Spaces

Author

Listed:
  • Broderick Crawford
  • Ricardo Soto
  • Gino Astorga
  • José García
  • Carlos Castro
  • Fernando Paredes

Abstract

In the real world, there are a number of optimization problems whose search space is restricted to take binary values; however, there are many continuous metaheuristics with good results in continuous search spaces. These algorithms must be adapted to solve binary problems. This paper surveys articles focused on the binarization of metaheuristics designed for continuous optimization.

Suggested Citation

  • Broderick Crawford & Ricardo Soto & Gino Astorga & José García & Carlos Castro & Fernando Paredes, 2017. "Putting Continuous Metaheuristics to Work in Binary Search Spaces," Complexity, Hindawi, vol. 2017, pages 1-19, May.
    • Handle: RePEc:hin:complx:8404231
    DOI: 10.1155/2017/8404231
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    References listed on IDEAS

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    1. Socha, Krzysztof & Dorigo, Marco, 2008. "Ant colony optimization for continuous domains," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1155-1173, March.
    2. Dyckhoff, Harald, 1990. "A typology of cutting and packing problems," European Journal of Operational Research, Elsevier, vol. 44(2), pages 145-159, January.
    3. Surafel Luleseged Tilahun & Hong Choon Ong, 2015. "Prey-Predator Algorithm: A New Metaheuristic Algorithm for Optimization Problems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 1331-1352, November.
    4. Tasgetiren, M. Fatih & Liang, Yun-Chia & Sevkli, Mehmet & Gencyilmaz, Gunes, 2007. "A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1930-1947, March.
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    Citations

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    Cited by:

    1. José García & Paola Moraga & Matias Valenzuela & Hernan Pinto, 2020. "A db-Scan Hybrid Algorithm: An Application to the Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    2. José García & Paola Moraga & Broderick Crawford & Ricardo Soto & Hernan Pinto, 2022. "Binarization Technique Comparisons of Swarm Intelligence Algorithm: An Application to the Multi-Demand Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 10(17), pages 1-20, September.
    3. Paulo Figueroa-Torrez & Orlando Durán & Broderick Crawford & Felipe Cisternas-Caneo, 2023. "A Binary Black Widow Optimization Algorithm for Addressing the Cell Formation Problem Involving Alternative Routes and Machine Reliability," Mathematics, MDPI, vol. 11(16), pages 1-23, August.
    4. José García & Victor Yepes & José V. Martí, 2020. "A Hybrid k-Means Cuckoo Search Algorithm Applied to the Counterfort Retaining Walls Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    5. Mauricio Castillo & Ricardo Soto & Broderick Crawford & Carlos Castro & Rodrigo Olivares, 2021. "A Knowledge-Based Hybrid Approach on Particle Swarm Optimization Using Hidden Markov Models," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    6. José García & José Lemus-Romani & Francisco Altimiras & Broderick Crawford & Ricardo Soto & Marcelo Becerra-Rozas & Paola Moraga & Alex Paz Becerra & Alvaro Peña Fritz & Jose-Miguel Rubio & Gino Astor, 2021. "A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    7. José García & José V. Martí & Víctor Yepes, 2020. "The Buttressed Walls Problem: An Application of a Hybrid Clustering Particle Swarm Optimization Algorithm," Mathematics, MDPI, vol. 8(6), pages 1-22, May.
    8. Marcelo Becerra-Rozas & José Lemus-Romani & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & José García, 2022. "Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector," Mathematics, MDPI, vol. 10(24), pages 1-30, December.
    9. José García & Gino Astorga & Víctor Yepes, 2021. "An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics," Mathematics, MDPI, vol. 9(3), pages 1-20, January.
    10. Sergio Valdivia & Ricardo Soto & Broderick Crawford & Nicolás Caselli & Fernando Paredes & Carlos Castro & Rodrigo Olivares, 2020. "Clustering-Based Binarization Methods Applied to the Crow Search Algorithm for 0/1 Combinatorial Problems," Mathematics, MDPI, vol. 8(7), pages 1-42, July.
    11. Marcelo Becerra-Rozas & José Lemus-Romani & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & Gino Astorga & Carlos Castro & José García, 2022. "Continuous Metaheuristics for Binary Optimization Problems: An Updated Systematic Literature Review," Mathematics, MDPI, vol. 11(1), pages 1-32, December.
    12. Michael J. Ryoba & Shaojian Qu & Ying Ji & Deqiang Qu, 2020. "The Right Time for Crowd Communication during Campaigns for Sustainable Success of Crowdfunding: Evidence from Kickstarter Platform," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    13. Michael J. Ryoba & Shaojian Qu & Yongyi Zhou, 2021. "Feature subset selection for predicting the success of crowdfunding project campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 671-684, September.

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