Finding good (or even just feasible) solutions for Mixed-Integer Nonlinear Programming problems independently of the specific problem structure is a very hard but practically important task, especially when the objective and/or the constraints are nonconvex. With this goal in mind, we present a general-purpose heuristic based on Variable Neighborhood Search, Local Branching, a local Nonlinear P...

There are varieties of QFD combination forms available that can help management to choose the right model for his/her types of problem. The proposed MOCC-QFD-FMEA model is a right model to include variety of objectives as well as the risk factors into the model of the problem. Due to the fact that the model also takes into consideration the concept of Fuzzy set, it further allows management...

In the paper a new approach to goal programming is presented: the robust approach, applied so far to a single-objective linear programming. It is a ”pessimistic” approach, meant to find a solution which will be reasonably good even in a bad case, but it is based on the assumption that almost never everything goes bad the decision maker can control and simulate the pessimistic aspect of the deci...

The concept of meta-goal programming is developed and linked to an interactive framework. An algorithm is proposed, in which the decision maker can establish target values on several achievement functions and use an interactive procedure to update these values. This substantially alleviates the problems associated with assigning to each attribute a target value, in order to build the goals, as ...