• journal_title：AAPG Bulletin
• Contributor：Stephen M. Rasey
• Publisher：American Association of Petroleum Geologists (AAPG)
• Date：2008-
• Format：text/html
• Language：en
• Identifier：10.1306/06040808068
• journal_abbrev：AAPG Bulletin
• issn：0149-1423
• volume：92
• issue：10
• firstpage：1337
• section：REGULAR ARTICLES

Portfolio optimization processes help managers understand the costs of achieving performance goals and the trade-offs in the performance of one business measure versus other business performance measures. A good portfolio optimization process makes it possible to negotiate goals and constraints on important key performance measures interactively and collaboratively, at the same time being fully aware of the price being paid to achieve one goal at the expense other goals. This article advocates a gradient search process, instead of a traditional linear programming or mixed integer linear programming methods to build thousands of optimum portfolios from an inventory of investment opportunities. The performance levels of those portfolios are then analyzed interactively with a visualization tool to negotiate collaboratively the trade-offs between goals and resource levels for the corporation or business unit.

The portfolio visualization process described in this article begins by asking asset managers to define different operational strategies and acceptable performance exchange rates for various key performance measures. Combinations of operational strategies and performance exchange rate strategies each create a portfolio strategy and a gradient in a multidimensional resource space. For each portfolio strategy, the gradient search (or greedy algorithm) creates dozens of optimum portfolios, each at different resource levels and with different results in key performance measures. Thousands of optimal candidate portfolios are created and stored, and the coupled visualization tool enables them to be interactively and collaboratively filtered. This powerful combination of technologies allows asset managers to explore the effects of resource constraints and performance goals at specified levels of confidence on dozens of key performance measures against thousands of potential portfolios generated by the gradient search. Managers can negotiate corporate and unit goals and budgets by knowing what portfolios are possible and what trade-offs exist between the unit's key performance measures. The visualization process allows managers to quickly select several portfolios they find equally acceptable and from those portfolios determine (1) which projects are common to all or most of the selected portfolios, indicating high priority; (2) which opportunities are members of only a few of the portfolios, indicating they are valuable but substitutable; and (3) which opportunities are absent from all the chosen portfolios and are thus low priority. The ability to quickly categorize the opportunities from a collection of superior portfolios gives managers high confidence in their investment decisions.