Abstract:

To formulate the fuzzy programming with piecewise linear membership function，a novel modeling methodology is proposed.By means of compatible configuration of binary variables，the relationship between the sub-membership functions is explicitly characterized，which helps the fuzzy optimization efficiently prevent the constraint-free problem happened in the general modeling methodologies，achieving satisfied optimal solutions.Additionally，compared with the conventional modeling methodologies，fewer binary items are required to model the membership function in some scenarios，possibly reducing the complexity of the calculations.In this paper，two methods consistent with this approach are introduced in detail，along with a numerical example employed to demonstrate the benefits of the contribution.