Annual production budget in the beverage industry

Luis Guimarães, Diego Klabjan, Bernardo Almada-Lobo*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Driven by a real-world application in the beverage industry, this paper provides a design of a new VNS variant to tackle the annual production budget problem. The problem consists of assigning and scheduling production lots in a multi-plant environment, where each plant has a set of filling lines that bottle and pack drinks. Plans also consider final product transfers between the plants. Our algorithm fixes setup variables for family of products and determines production, inventory and transfer decisions by solving a linear programming (LP) model. As we are dealing with very large problem instances, it is inefficient and unpractical to search the entire neighborhood of the incumbent solution at each iteration of the algorithm. We explore the sensitivity analysis of the LP to guide the partial neighborhood search. Dual-reoptimization is also used to speed-up the solution procedure. Tests with instances from our case study have shown that the algorithm can substantially improve the current business practice, and it is more competitive than state-of-the-art commercial solvers and other VNS variants.

Original languageEnglish (US)
Pages (from-to)229-241
Number of pages13
JournalEngineering Applications of Artificial Intelligence
Issue number2
StatePublished - Mar 2012


  • Beverage industry
  • Large neighborhood search
  • Long-term production planning
  • Mathematical programming
  • Multi-plant
  • Sensitivity analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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