Rapid parallel adaptive radiations from a single hybridogenic ancestral population

The Alpine lake whitefish (Coregonus lavaretus) species complex is a classic example of a recent radiation, associated with colonization of the Alpine lakes following the glacial retreat (less than 15 kyr BP). They have formed a unique array of endemic lake flocks, each with one to six described sympatric species differing in morphology, diet and reproductive ecology. Here, we present a genomic investigation of the relationships between and within the lake flocks. Comparing the signal between over 1000 AFLP loci and mitochondrial control region sequence data, we use phylogenetic tree-based and population genetic methods to reconstruct the phylogenetic history of the group and to delineate the principal centres of genetic diversity within the radiation. We find significant cytonuclear discordance showing that the genomically monophyletic Alpine whitefish clade arose from a hybrid swarm of at least two glacial refugial lineages. Within this radiation, we find seven extant genetic clusters centred on seven lake systems. Most interestingly, we find evidence of sympatric speciation within and parallel evolution of equivalent phenotypes among these lake systems. However, we also find the genetic signature of human-mediated gene flow and diversity loss within many lakes, highlighting the fragility of recent radiations.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.