Beta decay of 101Sn

The β decay of the very neutron-deficient isotope ¹⁰¹Sn was studied at the GSI on-line mass separator using silicon detectors for recording charged particles and germanium detectors for γ-ray spectroscopy. Based on the β-delayed proton data the production cross-section of ¹⁰¹Sn in the ⁵⁰Cr + ⁵⁸Ni fusion-evaporation reaction was determined to be about 60nb. The half-life of ¹⁰¹Sn was measured to be 1.9(3)s. For the first time β-delayed γ-rays of ¹⁰¹Sn were tentatively identified, yielding weak evidence for a cascade of 352 and 1065keV transitions in ¹⁰¹In. The results for the ¹⁰¹Sn decay as well as those from previous work on the ¹⁰³Sn decay are discussed by comparing them to predictions obtained from shell model calculations employing a new interaction in the ⁸⁸Sr to ¹³²Sn model space.     

Decay of 1.643 h <Superscript>95</Superscript>Ru and its daughter's level structure

The decay of ⁹⁵Ru has been investigated by means of γ-ray spectroscopy. The ⁹⁵Ru nuclei were produced by the reaction ⁹²Mo( α, n) ⁹⁵Ru at a beam energy of 17MeV. High-purity Ge detectors have been used singly and in coincidence to study γ-rays in the decay of ⁹⁵Ru to ⁹⁵Tc. 132 γ-rays are reported, among them, energies and intensities for 127 transitions have been determined. A decay scheme of ⁹⁵Ru with 31 levels is proposed which accommodates 127 of these transitions. Spins and parities for three new levels are proposed from calculated log ft values, measured γ-ray branching ratios, and in-beam experiment results of the daughter nucleus ⁹⁵Tc. Combining with the high-spin states observed by in-beam γ-ray spectroscopy of previous decay works, the structure of the excited states of ⁹⁵Tc is discussed in the framework of the projected shell model.     

Pullback attractors for a semilinear heat equation in a non-cylindrical domain

The existence and uniqueness of a variational solution satisfying energy equality is proved for a semilinear heat equation in a non-cylindrical domain with homogeneous Dirichlet boundary condition, under the assumption that the spatial domains are bounded and increase with time. In addition, the non-autonomous dynamical system generated by this class of solutions is shown to have a global pullback attractor.     

A sequential equality constrained quadratic programming algorithm for inequality constrained optimization

In this paper, the feasible type SQP method is improved. A new SQP algorithm is presented to solve the nonlinear inequality constrained optimization. As compared with the existing SQP methods, per single iteration, in order to obtain the search direction, it is only necessary to solve equality constrained quadratic programming subproblems and systems of linear equations. Under some suitable conditions, the global and superlinear convergence can be induced.     

Unification of lower-bound analyses of the lift-and-project rank of combinatorial optimization polyhedra

We present a unifying framework to establish a lower bound on the number of semidefinite-programming-based lift-and-project iterations (rank) for computing the convex hull of the feasible solutions of various combinatorial optimization problems. This framework is based on the maps which are commutative with the lift-and-project operators. Some special commutative maps were originally observed by Lovász and Schrijver and have been used usually implicitly in the previous lower-bound analyses. In this paper, we formalize the lift-and-project commutative maps and propose a general framework for lower-bound analysis, in which we can recapture many of the previous lower-bound results on the lift-and-project ranks.     

Stochastic optimal control and algorithm of the trajectory of horizontal wells

This paper presents a nonlinear, multi-phase and stochastic dynamical system according to engineering background. We show that the stochastic dynamical system exists a unique solution for every initial state. A stochastic optimal control model is constructed and the sufficient and necessary conditions for optimality are proved via dynamic programming principle. This model can be converted into a parametric nonlinear stochastic programming by integrating the state equation. It is discussed here that the local optimal solution depends in a continuous way on the parameters. A revised Hooke–Jeeves algorithm based on this property has been developed. Computer simulation is used for this paper, and the numerical results illustrate the validity and efficiency of the algorithm.     

Linearly constrained global optimization via piecewise-linear approximation

This paper considers the problem of optimizing a continuous nonlinear objective function subject to linear constraints via a piecewise-linear approximation. A systematic approach is proposed, which uses a lattice piecewise-linear model to approximate the nonlinear objective function on a simplicial partition and determines an approximately globally optimal solution by solving a set of standard linear programs. The new approach is applicable to any continuous objective function rather than to separable ones only and could be useful to treat more complex nonlinear problems. A numerical example is given to illustrate the practicability.     

A smoothing Newton-type method for generalized nonlinear complementarity problem

By using a new type of smoothing function, we first reformulate the generalized nonlinear complementarity problem over a polyhedral cone as a smoothing system of equations, and then develop a smoothing Newton-type method for solving it. For the proposed method, we obtain its global convergence under milder conditions, and we further establish its local superlinear (quadratic) convergence rate under the BD-regular assumption. Preliminary numerical experiments are also reported in this paper.     

Online scheduling with reassignment

This paper studies online scheduling problems with reassignment on two identical machines. We can reassign some jobs under certain rules after all the jobs have been assigned. Three different versions are studied and optimal algorithms are proposed.