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The Effect of Initial Population Sampling on the Convergence of Multi-Objective Genetic Algorithms

In: Multiobjective Programming and Goal Programming

Author

Listed:
  • Silvia Poles

    (ESTECO, Area Science Park—Padriciano)

  • Yan Fu

    (Ford Motor Company MD 2115)

  • Enrico Rigoni

    (ESTECO, Area Science Park—Padriciano)

Abstract

This paper aims to demonstrate that the initial population plays an important role in the convergence of genetic algorithms independently from the algorithm and the problem. Using a well-distributed sampling increases the robustness and avoids premature convergence. The observation is proved using MOGA-II and NSGA-II with different sampling methods. This result is particularly important whenever the optimization involves time-consuming functions.

Suggested Citation

  • Silvia Poles & Yan Fu & Enrico Rigoni, 2009. "The Effect of Initial Population Sampling on the Convergence of Multi-Objective Genetic Algorithms," Lecture Notes in Economics and Mathematical Systems, in: Vincent Barichard & Matthias Ehrgott & Xavier Gandibleux & Vincent T'Kindt (ed.), Multiobjective Programming and Goal Programming, pages 123-133, Springer.
  • Handle: RePEc:spr:lnechp:978-3-540-85646-7_12
    DOI: 10.1007/978-3-540-85646-7_12
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    Cited by:

    1. Validi, Sahar & Bhattacharya, Arijit & Byrne, P.J., 2014. "A case analysis of a sustainable food supply chain distribution system—A multi-objective approach," International Journal of Production Economics, Elsevier, vol. 152(C), pages 71-87.
    2. Cicconi, Paolo & Landi, Daniele & Germani, Michele & Russo, Anna Costanza, 2017. "A support approach for the conceptual design of energy-efficient cooker hoods," Applied Energy, Elsevier, vol. 206(C), pages 222-239.
    3. Mohammed Al-Turki & Arshad Jamal & Hassan M. Al-Ahmadi & Mohammed A. Al-Sughaiyer & Muhammad Zahid, 2020. "On the Potential Impacts of Smart Traffic Control for Delay, Fuel Energy Consumption, and Emissions: An NSGA-II-Based Optimization Case Study from Dhahran, Saudi Arabia," Sustainability, MDPI, vol. 12(18), pages 1-24, September.
    4. Chu Zhang & Tian Peng & Chaoshun Li & Wenlong Fu & Xin Xia & Xiaoming Xue, 2019. "Multiobjective Optimization of a Fractional-Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA-III Algorithm under Multiworking Conditions," Complexity, Hindawi, vol. 2019, pages 1-18, February.

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