Mehrabian et al. (Charnes et al. 1978) suggested as MAJ model for complete ranking efficient DMUs, but their approach lacks infeasibility in some cases, too.
Moreover, in the case when all the three system parameters are constrained simultaneously, the proposed approach outperforms the convex approaches in terms of infeasibility rate, PAPR, and bit error rate (BER) performances.
We equip these approaches with hyper-reduction techniques in the case of nonlinear flux and source terms, and also provide approaches for handling infeasibility.
Robust optimization approach allows for infeasibility in the control constraints by means of penalties.
In addition, the probability of infeasibility is very low, even when UE1 approaches the cell edge.
While aggregating and weighing individual preferences and viewpoints in one form or another towards any kind of social welfare is indispensable for collective policy-making and policy evaluation, Arrow showed the infeasibility of traditional economic approaches to preference aggregation (Arrow, 1970).
Thus, at the outset, it was deliberately decided not to base the whole programme on a supposedly precise quantitative forecast.1 In this specific situation, it was possible to explain the infeasibility of such an approach to policymakers, who naturally would have preferred a precise forecast.
Our performance results show the effectiveness of the proposed approach, which allows good performance with lower computational complexity and infeasibility rate than state-of-the-art PAPR-reduction convex approaches.
A direct approach, enforcing balance through hard constraints, may lead to infeasibility, but works well in practice.
To obviate the infeasibility of a full factorial based experimental approach to the intended exploration, an offline metamodel assisted optimization study within the same experimental range of the input/control variables was considered as a viable strategy.
Compared to other first-order methods for cone programs, our approach finds both primal and dual solutions when available and certificates of infeasibility or unboundedness otherwise, it does not rely on any explicit algorithm parameters, and the per-iteration cost of the method is the same as applying the splitting method to the primal or dual alone.
