Flexible design of commercial systems under market uncertainty: framework and application

A procedural framework is presented for the design optimization of modular commercial systems that are required to respond to changing market conditions. The basic premise is that commercial systems optimization aims directly at stakeholder value maximization. When stakeholder value is a quantifiable function of design variables and stochastic state variables, it can be maximized by maximizing expected value estimates plus the value from flexibility that stems from a design solution. We propose a multi-disciplinary framework, in which standard options valuation theory is used to model and valuate the flexibility embedded in a design solution, and external optimization techniques are used to determine the design of greatest value. We argue that the proposed framework is more intuitive and practical than equivalent stochastic optimization models. We demonstrate the framework in the preliminary design of the new Exploration Headquarters for British Petroleum in Aberdeen, Scotland. Preliminary results indicate that if flexibility is explicitly included in value-driven optimization, the resulting designs are quite dierent.

[1]  Natalia Ramirez,et al.  Valuing flexibility in infrastructure developments : the Bogota water supply expansion plan. , 2002 .

[2]  Curt Randall,et al.  Pricing Financial Instruments: The Finite Difference Method , 2000 .

[3]  Nikolaos V. Sahinidis,et al.  An Approximation Scheme for Stochastic Integer Programs Arising in Capacity Expansion , 2003, Oper. Res..

[4]  Andrew C. Lemer,et al.  INFRASTRUCTURE OBSOLESCENCE AND DESIGN SERVICE LIFE , 1996 .

[5]  Andrew C. Lemer,et al.  The fourth dimension in building : strategies for minimizing obsolescence , 1993 .

[6]  G. Friedl Copeland, Tom/Antikarov, Vladimir, Real Options. A Practitioner’s Guide, Texere LLC, New York 2001, $ 59,95 , 2002 .

[7]  T. Copeland Real Options: A Practitioner's Guide , 2001 .

[8]  L. Quigg Empirical Testing of Real Option‐Pricing Models , 1993 .

[9]  Eduardo S. Schwartz,et al.  Investment Under Uncertainty. , 1994 .

[10]  Jens Bengtsson,et al.  Manufacturing flexibility and real options: A review , 2001 .

[11]  Alexander J. Triantis,et al.  Valuing Flexibility as a Complex Option , 1990 .

[12]  Nalin Kulatilaka,et al.  The value of flexibility: The case of a dual-fuel industrial steam boiler , 1993 .

[13]  Nikolaos V. Sahinidis,et al.  Optimization under uncertainty: state-of-the-art and opportunities , 2004, Comput. Chem. Eng..

[14]  DETERMINING THE INFLUENCE OF DESIGN ATTRIBUTES ON CONSTRUCTION COST , 1995 .

[15]  Olivier L. de Weck,et al.  ENHANCING THE ECONOMICS OF COMMUNICATIONS SATELLITES VIA ORBITAL RECONFIGURATIONS AND STAGED DEPLOYMENT , 2003 .

[16]  Norman G. Miller,et al.  Commercial Real Estate Analysis and Investments , 2000 .

[17]  Shabbir Ahmed,et al.  A Multi-Stage Stochastic Integer Programming Approach for Capacity Expansion under Uncertainty , 2003, J. Glob. Optim..