NKD Group



Nonlinear Multiple Objective Programming: An optimization method that leads to more realistic ALM structure.  It incorporates the hierarchical and conflicting objectives that characterize many decision-problems. The method also incorporates true nonlinear relationships (demand functions, cost functions, and more. Commonly referred to as NLGP (nonlinear goal programming).

Genetic Algorithms: This method compliments NLGP methods.  Based on the survival of the fitness maxim, the genetic algorithm is extremely adept at optimizing an objective when the associated constraints are nonlinear and possibly discontinuous.

Discrete Optimization: discrete optimization methods are uniquely well suited to optimize complex large-scale capital investment problems. When combined with CVaR measures, simple solutions from highly complex constraint sets are possible.

Radial Basis Function Artificial Neural Networks: Artificial neural networks (ANN) are extremely accurate in their ability model complex, seemingly chaotic events. The radial basis function (RBF) approach produces extremely fast and accurate results.  The NKD Group is proud to be incorporate the vaunted Kajiji-4 RBF ANN for demand load forecasting, rate of return prediction, and volatility management.

Monte Carlo Simulation: An analytical technique for solving a problem by incorporating probabilistic estimates in a large number of simulation runs.  The solution to the complex decision-problem is inferred from the collective results of the trial runs.

Real Options Analysis: The application of derivatives theory to the operation and valuation of real capital investments.

Market Economics: The NKD Group offers integrated survey research services.  Our team has extensive experience in questionnaire design, pre-test, and sampling techniques.  We are experts in the analysis of survey data using advanced multivariate statistical tools and econometric models.  Our experience in this area ranges from customer perceptions in soup consumption, business planning, and forecasting future capital requirements based on residential demand for Internet services.


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