474 research outputs found

    Generalized relation between the relative entropy and dissipation for nonequilibrium systems

    Full text link
    Recently, Kawai, Parrondo, and Van den Broeck have related dissipation to time-reversal asymmetry. We generalized the result by considering a protocol where the physical system is driven away from an initial thermal equilibrium state with temperature β0\beta_0 to a final thermal equilibrium state at a different temperature. We illustrate the result using a model with an exact solution, i.e., a particle in a moving one-dimensional harmonic well.Comment: 4 page

    GASA-JOSH: a Hybrid Evolutionary-Annealing Approach for Job-Shop Scheduling Problem

    Full text link
    The job-shop scheduling problem is well known for its complexity as an NP-hard problem. We have considered JSSPs with an objective of minimizing makespan. In this paper, we develope a hybrid approach for solving JSSPs called GASA-JOSH. In GASA-JOSH, the population is divided in non-cooperative groups. Each group must refer to a method pool and choose genetic algorithm or simulated annealing to solve the problem. The best result of each group is maintained in a solution set, and then the best solution to the whole population is chosen among the elements of the solution set and reported as outcome. The proposed approach have been compared with other algorithms for job-shop scheduling and evaluated with satisfactory results on a large set of JSSPs derived from classical job-shop scheduling benchmarks. We have solved 23 benchmark problems and compared results obtained with a number of algorithms established in the literature

    An Effective Multi-Population Based Hybrid Genetic Algorithm for Job Shop Scheduling Problem

    Full text link
    The job shop scheduling problem is a well known practical planning problem in the manufacturing sector. We have considered the JSSP with an objective of minimizing makespan. In this paper, a multi-population based hybrid genetic algorithm is developed for solving the JSSP. The population is divided in several groups at first and the hybrid algorithm is applied to the disjoint groups. Then the migration operator is used. The proposed approach, MP-HGA, have been compared with other algorithms for job-shop scheduling and evaluated with satisfactory results on a set of JSSPs derived from classical job-shop scheduling benchmarks. We have solved 15 benchmark problems and compared results obtained with a number of algorithms established in the literature. The experimental results show that MP-HGA could gain the best known makespan in 13 out of 15 problems

    JOSIS' 10th anniversary special feature: part two

    Full text link

    Surface reconstructions and premelting of the (100) CaF2 surface

    Get PDF
    In this work, surface reconstructions on the (100) surface of CaF2 are comprehensively investigated. The configurations were explored by employing the Minima Hopping Method (MHM) coupled to a machine-learning interatomic potential, that is based on a charge equilibration scheme steered by a neural network (CENT). The combination of these powerful methods revealed about 80 different morphologies for the (100) surface with very similar surface formation energies differing by not more than 0.3 J m−2. To take into account the effect of temperature on the dynamics of this surface as well as to study the solid–liquid transformation, molecular dynamics simulations were carried out in the canonical (NVT) ensemble. By analyzing the atomic mean-square displacements (MSD) of the surface layer in the temperature range of 300–1200 K, it was found that in the surface region the F sublattice is less stable and more diffusive than the Ca sublattice. Based on these results we demonstrate that not only a bulk system, but also a surface can exhibit a sublattice premelting that leads to superionicity. Both the surface sublattice premelting and surface premelting occur at temperatures considerably lower than the bulk values. The complex behaviour of the (100) surface is contrasted with the simpler behavior of other low index crystallographic surfaces

    A fingerprint based metric for measuring similarities of crystalline structures

    Get PDF
    Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not suitable as fingerprints to distinguish structures. Based on a characterization of the local environment of all atoms in a cell we introduce crystal fingerprints that can be calculated easily and allow to define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures. The new method is an useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms and high-throughput screenings
    corecore