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A Hybrid Projected Gradient-Evolutionary Search Algorithm for Capacitated Multi-Source Multiuavs Scheduling with Time Windows

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Recent Developments in Cooperative Control and Optimization

Part of the book series: Cooperative Systems ((COSY,volume 3))

Abstract

The objective of this effort is to develop a hybrid evolutionary-gradient based technique to overcome the combinatorial complexity when solving large scale mixed integer nonlinear optimization problems. The basic idea relies on combining genetic algorithms (GA) and gradient projection method to exploit their complementary strengths. The effectiveness of these strategies are illustrated in the area of capacitated multi-source multi-vehicle scheduling with time windows.

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Author information

Authors and Affiliations

  1. NASA-ACIT Center Dept. of E&CE, NC A&T State University, USA

    Ali Ahmadzadeh & Abdollah Homaifar (Duke Energy Eminent Professor)

  2. Pavilion Technologies, Inc, Austin, TX, USA

    Bijan Sayyar-Roudsari

Authors
  1. Ali Ahmadzadeh
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  2. Bijan Sayyar-Roudsari
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  3. Abdollah Homaifar
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Editor information

Editors and Affiliations

  1. Texas A&M University, College Station, Texas, USA

    Sergiy Butenko

  2. Air Force Research Laboratory, Eglin, Florida, USA

    Robert Murphey

  3. University of Florida, Gainsville, Florida, USA

    Panos M. Pardalos

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© 2004 Kluwer Academic Publishers

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Ahmadzadeh, A., Sayyar-Roudsari, B., Homaifar, A. (2004). A Hybrid Projected Gradient-Evolutionary Search Algorithm for Capacitated Multi-Source Multiuavs Scheduling with Time Windows. In: Butenko, S., Murphey, R., Pardalos, P.M. (eds) Recent Developments in Cooperative Control and Optimization. Cooperative Systems, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0219-3_1

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  • DOI: https://doi.org/10.1007/978-1-4613-0219-3_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7947-8

  • Online ISBN: 978-1-4613-0219-3

  • eBook Packages: Springer Book Archive

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