The fourth step is to verify the assumptions, which are the conditions that make your problem suitable for linear programming. The main assumptions are that the objective function and the ...

The second step to debug a LP model is to check the data input, that is, the values of the parameters and the coefficients. You should make sure that the data input is consistent, realistic, and ...

Steps followed for formulating Linear Programming model [3] [17] [20] • Identifying and defining the decision variable of the given problem. • Defining the objective function. • Stating the ...

This paper deals with a fuzzy goal programming methodology for solving multiobjective linear fractional chance constrained programming problems containing fuzzy numbers and exponentially distributed ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...

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 ...

The MINLP model aims to minimize the total PV power curtailment while considering the technical operation of the distribution network. First, a nonlinear mathematical formulation is presented. Then, a ...

Linear programming (LP) problems are ubiquitous in various real-world scenarios. OptimouseQuest aims to facilitate the development of conversational agents that assist users in formulating linear ...

Askari-Nasab et al. proposed an approach based on Fuzzy Logic Clustering (FLC) to generate mining cuts from an iron ore deposit and input them into a production scheduling model based on Mixed Integer ...

The computational protein design problem or the side-chain positioning problem is a central part in computational methods for predicting protein structure and designing protein sequences. However, the ...