Info-Gap Decision Theory | Voodoo Decision-Making | Robust Decisions | Severe Uncertainty | Satisficing vs Optimizing | Maximin


Composite Concave Linear Programming (CCLP)

In the early 1980s I began a research effort whose aim is to find remedies for the impact of the Curse of Dimensionality on dynamic programming in cases where the objective function of the optimization problem is not separable (in a dp sense).

This lead to the formulation of a new nonlinear programming method that I called Composite Concave Programming (CP). The title reflects the fact that the method is designed for case where the objective function is composite and concave in nature.

However, from the outset it was crystal clear to me that the main area of application of CP will be linear programming rather than dynamic programming. This is an obvious implication of the fact that the Simplex Method of linear programming provides extremely useful parametric programming facilities, in fact exactly the type of facilities that are required for successful implementation of CCP.

CCLP is then the special case of CP associated with problems whose constraints are linear and the objective function is a composite concave function of two linear functions. There are many practical problems of this type.

I created the CCLP site for two main purposes:

  1. OR/MS Lecturers
    CCLP offers excellent teaching material to supplement conventional topics in linear and non-linear optimization.
  2. OR/MS Software Developers
    CCLP offers LP/QP software developers excellent opportunities to enlarge the scope of operation of their product.

I am now in the process of writing a short book on CCLP. Hopefully this will encourage sceptical lectures/software developers to look seriously at this matter.


Disclaimer: This page, its contents and style, are the responsibility of the author (Moshe Sniedovich) and do not represent the views, policies or opinions of The University of Melbourne.

Disclaimer: This page, its contents and style, are the responsibility of the author (Moshe Sniedovich) and do not represent the views, policies or opinions of the organizations he is associated/affiliated with.