The purple curve represents the trade-off curve in the objective space. It is formed by mapping the optimal solutions obtained as the weight w1 changes, showing how improving one objective comes at the expense of the other.
Conditions: At least two objectives are plotted against each other.; Solutions are generated for multiple weight values.
The purple curve represents the trade-off curve in the objective space. It is formed by mapping the optimal solutions obtained as the weight w1 changes, showing how improving one objective comes at the expense of the other.
Conditions: At least two objectives are plotted against each other.; Solutions are generated for multiple weight values.
The Pareto front is the curve that links all non-dominated solutions in the objective-value plot. Visually, it is the lower-left boundary of the attainable set in this minimization problem, representing the best possible trade-offs between the conflicting objectives.
Conditions: Objectives are plotted in the (OBJ_1, OBJ_2) plane.; The example uses minimization of both objectives.
The Pareto front is the curve that links all non-dominated solutions in the objective-value plot. Visually, it is the lower-left boundary of the attainable set in this minimization problem, representing the best possible trade-offs between the conflicting objectives.
Conditions: Objectives are plotted in the (OBJ_1, OBJ_2) plane.; The example uses minimization of both objectives.
The weight table serves as the computational scaffold for exploring the family of weighted problems. It lists candidate values for the weight w1, allowing the user to compute the aggregate objective J and record the resulting objective values OBJ1 and OBJ2 for each weight choice.
Conditions: Use a set of candidate weights w1.; Compute J for each weight.; Record the resulting solution’s OBJ1 and OBJ2 values.
The weight table serves as the computational scaffold for exploring the family of weighted problems. It lists candidate values for the weight w1, allowing the user to compute the aggregate objective J and record the resulting objective values OBJ1 and OBJ2 for each weight choice.
Conditions: Use a set of candidate weights w1.; Compute J for each weight.; Record the resulting solution’s OBJ1 and OBJ2 values.