Linear solution schemes for Mean-SemiVariance Project portfolio selection problems: An application in the oil and gas industry

Jorge Sefair, Carlos Y. Méndez, Onur Babat, Andrés L. Medaglia, Luis F. Zuluaga

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

We study the Mean-SemiVariance Project (MSVP) portfolio selection problem, where the objective is to obtain the optimal risk-reward portfolio of . non-divisible projects when the risk is measured by the semivariance of the portfolio's Net-Present Value (NPV) and the reward is measured by the portfolio's expected NPV. Similar to the well-known Mean-Variance portfolio selection problem, when integer variables are present (e.g., due to transaction costs, cardinality constraints, or asset illiquidity), the MSVP problem can be solved using Mixed-Integer Quadratic Programming (MIQP) techniques. However, conventional MIQP solvers may be unable to solve large-scale MSVP problem instances in a reasonable amount of time. In this paper, we propose two . linear solution schemes to solve the MSVP problem; that is, the proposed schemes avoid the use of MIQP solvers and only require the use of Mixed-Integer Linear Programming (MILP) techniques. In particular, we show that the solution of a class of real-world MSVP problems, in which project returns are positively correlated, can be accurately approximated by solving a single MILP problem. In general, we show that the MSVP problem can be effectively solved by a sequence of MILP problems, which allow us to solve large-scale MSVP problem instances faster than using MIQP solvers. We illustrate our solution schemes by solving a real MSVP problem arising in a Latin American oil and gas company. Also, we solve instances of the MSVP problem that are constructed using data from the PSPLIB library of project scheduling problems.

Original languageEnglish (US)
JournalOmega (United Kingdom)
DOIs
StateAccepted/In press - Aug 18 2014

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Keywords

  • Benders decomposition
  • Mean-SemiVariance
  • Petroleum industry
  • Project portfolio optimization
  • Project selection
  • Risk
  • Semivariance

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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