Optimal distribution-inventory planning of industrial gases. I. Fast computational strategies for large-scale problems

Fengqi You, Jose M. Pinto, Elisabet Capón, Ignacio E. Grossmann, Nikhil Arora, Larry Megan

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

In this paper, we address the optimization of industrial gas distribution systems, which consist of plants and customers, as well as storage tanks, trucks, and trailers. A mixed-integer linear programming (MILP) model is presented to minimize the total capital and operating costs, and to integrate short-term distribution planning decisions for the vehicle routing with long-term inventory decisions for sizing storage tanks at customer locations. In order to optimize asset allocation in the industrial gas distribution network by incorporating operating decisions, the model also takes into account the synergies among delivery schedule, tank sizes, customer locations, and inventory profiles. To effectively solve large-scale instances, we propose two fast computational strategies. The first approach is a two-level solution strategy based on the decomposition of the full-scale MILP model into an upper level route selection-tank sizing model and a lower level reduced routing model. The second approach is based on a continuous approximation method, which estimates the operational cost at the strategic level and determines the trade-off with the capital cost from tank sizing. Three case studies including instances with up to 200 customers are presented to illustrate the applications of the models and the performance of the proposed solution methods.

Original languageEnglish (US)
Pages (from-to)2910-2927
Number of pages18
JournalIndustrial and Engineering Chemistry Research
Volume50
Issue number5
DOIs
StatePublished - Mar 2 2011

ASJC Scopus subject areas

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

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