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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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An Effective Evolutionary Hybrid for Solving the Permutation Flowshop Scheduling Problem.

Mehrdad Amirghasemi1, Reza Zamani2

  • 1Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia mehrdad@uow.edu.au.

Evolutionary Computation
|July 30, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces an evolutionary hybrid algorithm for the permutation flowshop scheduling problem. The novel approach enhances solution quality by focusing on critical paths and outperforms existing methods.

Keywords:
Genetic algorithmsbiased random samplingconstruction methods.hybridsmemetic algorithmspermutation flowshop scheduling

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Area of Science:

  • Operations Research
  • Computer Science
  • Computational Intelligence

Background:

  • The permutation flowshop scheduling problem (PFSP) is a complex combinatorial optimization challenge.
  • Existing methods often struggle to efficiently find optimal or near-optimal solutions for PFSP.
  • Effective scheduling is crucial for manufacturing efficiency and cost reduction.

Purpose of the Study:

  • To develop and evaluate a novel evolutionary hybrid algorithm for solving the PFSP.
  • To improve the quality of solutions generated for PFSP instances.
  • To investigate the synergistic effects of different algorithmic components.

Main Methods:

  • A memetic algorithm framework incorporating a novel construction component.
  • Utilizing a reblocking mechanism with biased random sampling to prioritize short processing times on the critical path.
  • Employing 2-exchange swap and insertion local searches, guided by the critical path concept, for solution refinement.
  • Systematic computational experiments on benchmark PFSP instances.

Main Results:

  • The proposed evolutionary hybrid demonstrates superior performance compared to several state-of-the-art procedures on benchmark instances.
  • The integration of the construction component and local search mechanisms shows strong synergy.
  • Analysis confirms the effectiveness of critical path-based strategies in enhancing solution quality.

Conclusions:

  • The developed evolutionary hybrid is a robust and effective procedure for the permutation flowshop scheduling problem.
  • The critical path notion is a valuable concept for exploiting PFSP structure within evolutionary algorithms.
  • The findings offer a significant advancement in solving complex scheduling problems.