Pareto Optimization

In many conflicts, a single measure (often, money) suffices to resolve all issues. Car buyers want the lowest price while sellers want the highest; management wants the lowest wage, while labor wants the highest.

In other cases, there are multiple issues but difficulty in treating them all on the same scale. Consider a conflict over development of a ski area in old growth forest that provides water to a neighboring town and raises issues of endangered species, forest fires, jurisdiction, pollution, soil erosion, privatization of government land, and differing opinions on the proper roles of government. The conflict not only divides citizens, but also pits businesses, environmental groups, and federal, state, and local government agencies against one another.

In 1906, Pareto (1971) proposed a method for identifying the most efficient solutions to such multiple criteria and multiple party conflicts. A solution is “Pareto optimal” if there is no other solution that performs at least as well on every criterion and is strictly better on at least one. Visualize this as a scatterplot of all possible solutions on a graph in which each criterion is represented by a separate axis. In a two-criteria problem, both of which are to be maximized (e.g., a car that is both safe and fuel-efficient), optimal solutions lie along a line with no points above it. Of course, sometimes the goal is to minimize both criteria (a car that is inexpensive and quick to produce), and in others the goal is to minimize one criterion (production time) and maximize the other (fuel efficiency). As the number of criteria increase, it becomes difficult to visualize the situation, but it remains solvable mathematically.

Completing a Pareto analysis in preparation for an arbitration, mediation, or negotiation enables one to design offers and counteroffers and to assess those of opponents against one’s own objectives (Chapter 17). It is one possible method for making good and avoiding bad decisions in many situations.