Researchers utilize mixed-integer linear programming and nonlinear programming formulations for neural networks, tree ensembles, and decision trees. (9,35,36) Additionally, several tools such as the ...

It is anticipated that, in many instances, this breeding objective would be transformed from a ratio to some linear function (i.e., income - expense). There is no guarantee that this transformation ...

Large-scale many-objective optimization problems (LSMaOPs) pose great difficulties for traditional evolutionary algorithms due to their slow search for Pareto-optimal solutions in huge decision space ...

In many real-life situations, it is necessary to optimize two or more objects simultaneously. In such problems, the objectives under consideration conflict with each other, and optimizing a solution ...

Objective Function: Linear function Z = ax + by, where a and b are constants, which has to be maximised or minimised is called a linear objective function. Decision Variables: In the objective ...

Decision Variables In the objective function Z = ax + by, x and y are called decision variables. Constraints The linear inequalities or restrictions on the variables of an LPP are called constraints.