This paper presents a unit commitment algorithm that defines each unit discharge given the water head, the total plant downstream flow, the variable discharge upper limit, the unit efficiency curves, and the restricted operating zones in order to maximize power efficiency. This algorithm is part of the preprocessing phase that is intended to approximate a hydro-power production function that represents individualized unit decisions. A compact mixed-integer linear programming formulation, with fewer integer variables, based on an equivalent unit model and a piecewise linear generation function, is proposed. The unit commitment is integrated without increasing the model size and complexity due to the preprocessing phase. Moreover, the optimal aggregate decision is automatically converted to unit decisions by the proposed algorithm. The coordination with mid/long-term planning is performed by taking into account the power demand allocated to the hydro-power plants. Numerical tests on Brazilian hydro-power plants demonstrate that the proposed formulation has lower computational cost than unit individualized models considering a given accuracy level for the generation function approximation.

This paper presents a multi-objective evolutionary algorithm based on decomposition (MOEA/D) to design broadband optimal Yagi-Uda antennas. A multi-objective problem is formulated to achieve maximum directivity, minimum voltage standing wave ratio and maximum front-to-back ratio. The algorithm was applied to the design of optimal 3 to 10 elements Yagi-Uda antennas, whose optimal Pareto fronts are provided in a single picture. The multi-objective problem is decomposed by Chebyshev decomposition, and it is solved by differential evolution (DE) and Gaussian mutation operators in order to provide a better approximation of the Pareto front. The results show that the implemented MOEA/D is efficient for designing Yagi-Uda antennas.

This paper proposes a new reconfiguration heuristic in order to reduce the total power loss and the maximum current of electrical radial networks. It is based on the branch-and-bound strategy, which is an implicit enumeration method that uses a tree structure and bounds to organize the searching process. The search tree in this paper is constructed by subdividing the feasible set using the branch-exchange technique in the networks. The constraints and the Pareto dominance are responsible for pruning the search tree. The heuristic also returns a feasible switching plan for each solution. The algorithm was successfully applied to medium- and large-scale problems.