Skip to main content

Genetic Algorithms for BATCH Process Scheduling Using BHA and MILP Formulation

  • Chapter
Bayesian Heuristic Approach to Discrete and Global Optimization

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 17))

  • 425 Accesses

Abstract

So far we have described two ways of applying BHA to the Batch Scheduling Problem. In Chapter 14 specific MRP heuristics were used. In Chapter 15 the SA ”initial temperature” parameter was optimized while applying the MIBLP penalized profit function as a heuristic.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Mockus, J., Eddy, W., Mockus, A., Mockus, L., Reklaitis, G. (1997). Genetic Algorithms for BATCH Process Scheduling Using BHA and MILP Formulation. In: Bayesian Heuristic Approach to Discrete and Global Optimization. Nonconvex Optimization and Its Applications, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2627-5_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-2627-5_16

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4767-3

  • Online ISBN: 978-1-4757-2627-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics