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OR Practice—Solving Complex Chemical Equilibria Using a Geometric-Programming Based Technique

Author

Listed:
  • Thomas Wayne Wall

    (C.A.C.I., Newport Beach, California)

  • Doran Greening

    (Otis Elevator, Denver, Colorado)

  • R. E. D. Woolsey

    (Colorado School of Mines, Golden, Colorado)

Abstract

Determining the composition of a chemical system at equilibrium is an important problem that arises in many fields of science and engineering. For complex equilibria, the use of a digital computer is required. The chemist often finds the use of current computer codes an inefficient and frustrating experience. This paper presents a globally convergent algorithm for the solution of chemical equilibrium problems. This algorithm has been made both efficient and easy to use and is now employed successfully by chemists on important problems. It is based on the application of geometric programming principles to solve systems of nonlinear equations. Although presented in a form that can be quickly understood by the practitioner, the methodology is mathematically rigorous. Computer programs that require no familiarity with the details of the methodology were developed and extensively tested. These programs can be used as general research tools for investigating the solution of nonlinear equations in areas other than chemistry.

Suggested Citation

  • Thomas Wayne Wall & Doran Greening & R. E. D. Woolsey, 1986. "OR Practice—Solving Complex Chemical Equilibria Using a Geometric-Programming Based Technique," Operations Research, INFORMS, vol. 34(3), pages 345-355, June.
    • Handle: RePEc:inm:oropre:v:34:y:1986:i:3:p:345-355
    DOI: 10.1287/opre.34.3.345
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    Cited by:

    1. Leyla Aliabadi & Seyed Hessameddin Zegordi & Ali Husseinzadeh Kashan & Mohammad Ali Rastegar, 2024. "A sustainable supply chain model for time-varying deteriorating items under the promotional cost-sharing policy and three-level trade credit financing," Operational Research, Springer, vol. 24(2), pages 1-59, June.
    2. Rashed Khanjani-Shiraz & Salman Khodayifar & Panos M. Pardalos, 2021. "Copula theory approach to stochastic geometric programming," Journal of Global Optimization, Springer, vol. 81(2), pages 435-468, October.

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