Analysis of Multi-objective Hyper-Heuristics Under Different Dynamic and Preferential Environments

Authors

  • Teodoro Macias TecNM
  • Laura Cruz-Reyes Graduate Program Division, Tecnológico Nacional de México, Instituto Tecnológico de Ciudad Madero, Cd. Madero 89440, Mexico
  • Bernabé Dorronsoro Departamento de Ingeniería Informática, Universidad de Cádiz, 11519 Puerto Real, Spain
  • Claudia Gómez-Santillán Graduate Program Division, Tecnológico Nacional de México, Instituto Tecnológico de Ciudad Madero, Cd. Madero 89440, Mexico

Keywords:

Hyper-heuristic, Dynamic Optimization, Multi-objective Optimization, Preference Incorporation

Abstract

The use of hyper-heuristics to solve dynamic multi-objective optimization problems (DMOPs) that incorporate decision-maker's preferences is a recently addressed research area. This paper proposes the analysis and comparison of three hyper-heuristics to solve preferential DMOPs. The Dynamic Hyper-Heuristic with Plane Separation (DHH-PS), a previously proposed methodology using Plane Separation (PS), a reference-point-based preference incorporation method. This paper also proposes two versions of the Dynamic Population-Evolvability based Multi-objective Hyper-Heuristic (DPEM-HH), incorporating PS and different low-level heuristics sets. This work tests DHH-PS and both DPEM-HH-PS versions under multiple dynamic and preferential environments, seeking to extend the study of DHH-PS and analyze the capability of DPEM-HH-PS. DPEM-HH-PS exhibited suitability for type II DMOPs and randomly-changing instances. DHH-PS presented a better performance for tri-objective DMOPs. The combination of genetic algorithms and differential evolution in DPEM-HH-PS proved effective for solving preferential DMOPs. DHH-PS and DPEM-HH-PS were capable of adapting to different preferential and dynamic environments.

Published

2022-08-15

How to Cite

Macias, T., Cruz-Reyes, L., Dorronsoro, B., & Gómez-Santillán, C. (2022). Analysis of Multi-objective Hyper-Heuristics Under Different Dynamic and Preferential Environments. International Journal of Combinatorial Optimization Problems and Informatics, 13(2), 1–13. Retrieved from https://www.ijcopi.org/ojs/article/view/264

Issue

Section

SI Business Analytics

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