A hierarchical Lagrangean relaxation procedure for solving midterm planning problems

Anshuman Gupta, Costas D. Maranas

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


An efficient decomposition procedure for solving midterm planning problems is developed based on Lagrangean relaxation. The basic idea of the proposed solution technique is the successive partitioning of the original problem into smaller, more computationally tractable subproblems by hierarchical relaxation of key complicating constraints. The systematic identification of these complicating constraints is accomplished by utilizing linear programming relaxation dual-multiplier information. This hierarchical Lagrangean relaxation procedure, along with an upper bound generating heuristic, is incorporated within a subgradient optimization framework. This solution strategy is found to be much more effective, in terms of both quality of solution and computational requirements, than commercial mixed- integer linear programming solvers in bracketing the optimal value, especially for larger problems.

Original languageEnglish (US)
Pages (from-to)1937-1947
Number of pages11
JournalIndustrial and Engineering Chemistry Research
Issue number5
StatePublished - 1999

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering


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