Fuzzy regression models are useful to investigate the relationship between explanatory and response variables with fuzzy observations. Different from previous studies, this correspondence proposes a ...

There is a need for design strategies that can support rapid and widespread deployment of new energy systems and process technologies. In a previous work, we introduced process family design as an ...

Modeling Using Linear Programming Cengage Supplementary Chapter C: Modeling Using Linear Programming C3 DEVELOPING LINEAR OPTIMIZATION MODELS To introduce the basic concepts of optimization ...

In this paper, we consider the application of a nonlinear programming (NLP) approach for solving the optimal control problem, using the single and multiple shooting methods in formulation of the NLP ...

3. Methodology The framework developed for this approach uses a mixed-integer linear programming formulation, balancing imprecision from linearization with benefits of global optima and rapid ...

Information Geometry Formulation of Latent Linear Models An implementation of a variety of information geometry formulation of latent linear models. This impleentation is based on the following paper.

Step 4: Taking minimal acceptance degree and maximal degree of rejection, formulate the following equivalent ordinary Linear programming problem: (12) where, are the membership of the objective and ...

Discover a groundbreaking technique for solving binary linear programming models in polynomial time. Explore the transformation into convex quadratic programming and the use of interior point ...