Optimization by simulating molecular evolution

Based on the analogy between mathematical optimization and molecular evolution and on Eigen's quasi-species model of molecular evolution, an evolutionary algorithm for combinatorial optimization has been developed. This algorithm consists of a versatile variation scheme and an innovative decision rule, the essence of which lies in a radical revision of the conventional philosophy of optimization: A number of configurations of variables with better values, instead of only a single best configuration, are selected as starting points for the next iteration. As a result the search proceeds in parallel along a number of routes and is unlikely to get trapped in local optima. An important innovation of the algorithm is introduction of a constraint to let the starting points always keep a certain distance from each other so that the search is able to cover a larger region of space effectively. The main advantage of the algorithm is that it has more chances to find the global optimum and as many local optima as possible in a single run. This has been demonstrated in preliminary computational experiments.     

The cytogenetics of domestic geese

Hybrids were produced between an African male and several Pilgrim female domestic geese. Partial karyotypes revealed a difference in the fourth largest pair of autosomal chromosomes. This chromosome pair was metacentric in the African, submetacentric in the Pilgrim, and heteromorphic in the hybrids. A similar difference between the putative wild ancestors of the African and Pilgrim breeds has been reported by others. These findings provide cytological evidence to support the traditional opinion that the African breed was derived from the Asiatic swan goose (Anser cygnoides) and the Pilgrim breed was derived from the European greylag goose (Anser anser).