Recently I posted two blogs on the topic of Constraint Satisfaction (Part 1, Part 2). I'm still interested in this topic and did some more searching last night to see what additional useful material I could dig up on the topic of constraints.

One recent resource that looks interesting is a book by Adam Morgan and Mark Barden called A Beautiful Constraint (2015). According to their website, "A Beautiful Constraint calls for constraint–driven problem–solving to become a much more widespread capability and offers an original framework to achieve that". Reviews for the book so far are quite good.

Another resource is an MIT Thesis by Mark Donald Gross called Design As Exploring Constraints (1985). This freely available manuscript is useful because it directly addresses the role of constraints in design, indeed, it views design as an exploration of constraints. While the technology discussed is dated, the discussion around design as exploring constraints is not.

A popular approach to thinking about constraints is via the Theory of Constraints popularized by Eliyahu M. Goldratt in his book The Goal (1986). In this theory business growth is viewed as a process of identifying and overcoming a constraint that is currently holding a company back from growing. Once that constraint is addressed a new constraint will be revealed as the limiting factor which in turn will have to be addressed and so. The theory of constraints is popular in the lean production literature. This view of growth is similiar to the Law of the Minimum which I discussed in a previous blog.

A final noteworthy resource was discussed by Mark Gross in his thesis, namely a book by Nobel Laureate Herb Simon called Sciences of the Artificial (1996). This is a seminal book on "Design Science" in which Herb Simon argues for a view of design as "optimizing an objective function over a region bounded by constraints" (Gross, p. 140). The optimization that is going on here, however, is quite subtle because Herb Simon views such optimization as a matter of "satisficing" or finding a "good enough solution" rather than a solution that would require unrealistic amounts of computing power. There is a threshold to the amount of work we'll do to arrive at our view on what the optimal design is. So while we may in fact arrive at an optimal solution to a set of constraints when we can formulate the problem in quantitative terms, in most cases we are using a different approach to optimizing our objective function, one in which we will be satisfied with a good enough solution if it means being able to operate within time and resource constraints at hand.

The purpose of this blog is to identify some more literature worth exploring to clarify the role and nature of constraints in design and business.