In the framework of central receiver solar plants, the heliostat field can take up to 50% of the initial investment and cause up to 40% of energy loss. The most popular design strategies are based on: (i) forcing heliostats to follow known distribution patterns and (ii) iterative selection of positions. However, these methods might produce suboptimal solutions. The evolution of computational platforms allows the development of more flexible approaches. In this work, Hector, a new meta-heuristic aimed at facilitating coordinate-based optimization, is presented. First, since East-West symmetry is imposed, one of those regions is ignored and the number of heliostats to be placed is halved. Second, the selected region is split into separate circular sectors around the receiver. Next, at every iteration, a new heliostat is added to the most promising sector. Then, it is optimized by a user-selected algorithm, as an independent problem, in a continuous search-space. This procedure is repeated until all the required heliostats have been deployed. The computed half is finally cloned into the other one. Two versions of this strategy are proposed. Our empirical results show that, for a given optimizer, better fields are obtained with Hector. The second version yields the best fields but requires more runtime
