Comparing routines for the numerical solution of initial value problems of ordinary differential equations in multiple shooting

Summary The numerical solution of two-point boundary value problems and problems of optimal control by shooting techniques requires integration routines. By solving 15 real-life problems four well-known intergrators are compared relative to reliability, fastness and precision. Hints are given, which routines could be used for a problem.     

Complex differential games of pursuit-evasion type with state constraints,part 1: Necessary conditions for optimal open-loop strategies

Complex pursuit-evasion games with state variable inequality constraints are investigated. Necessary conditions of the first and the second order for optimal trajectories are developed, which enable the calculation of optimal open-loop strategies. The necessary conditions on singular surfaces induced by state constraints and non-smooth data are discussed in detail. These conditions lead to multi-point boundary-value problems which can be solved very efficiently and very accurately by the multiple shooting method. A realistically modelled pursuit-evasion problem for one air-to-air missile versus one high performance aircraft in a vertical plane serves as an example. For this pursuit-evasion game, the barrier surface is investigated, which determines the firing range of the missile. The numerical method for solving this problem and extensive numerical results will be presented and discussed in Part 2 of this paper; see Ref. 1.This paper is dedicated to the memory of Professor John V. Breakwell.The authors would like to express their sincere and grateful appreciation to Professors R. Bulirsch and K. H. Well for their encouraging interest in this work.     

Density of states in type-II superconductors in high magnetic fields

Using the Gorkov theory as modified by Eilenberger we derive a consistent calculation scheme for the density of states near the upper critical field. This method applies to arbitrary impurity concentration and becomes in particular simple in the clean limit. Special attention was paid to the effect of anisotropic impurity scattering (p-waves).     

Numerical treatment of delay differential equations by Hermite Interpolation

Summary A class of numerical methods for the treatment of delay differential equations is developed. These methods are based on the wellknown Runge-Kutta-Fehlberg methods. The retarded argument is approximated by an appropriate multipoint Hermite Interpolation. The inherent jump discontinuities in the various derivatives of the solution are considered automatically.Problems with piecewise continuous right-hand side and initial function are treated too. Real-life problems are used for the numerical test and a comparison with other methods published in literature.     

A Lagrangian lower bound for the container transshipment problem at a railway hub for a fast branch-and-bound algorithm

In this paper, we consider the container transshipment problem at a railway hub. A simple lower bound known for this problem will be improved by a new Lagrangian relaxation lower bound. Computational tests show that this lower bound outperforms the simple one and decreases substantially the run time of the branch-and-bound algorithm.     

Interface properties of the three-state potts model in two dimensions

Interface properties, in particular the interface free energy and the interface profile of the three-state Potts model in two dimensions are studied using Monte Carlo techniques and a generalized version of the method of Müller-Hartmann and Zittartz. The role of the third state in characterizing the interface between the two other states is elucidated.     

A branch-and-bound algorithm for the resource-constrained project scheduling problem

We describe a time-oriented branch-and-bound algorithm for the resource-constrained project scheduling problem which explores the set of active schedules by enumerating possible activity start times. The algorithm uses constraint-propagation techniques that exploit the temporal and resource constraints of the problem in order to reduce the search space. Computational experiments with large, systematically generated benchmark test sets, ranging in size from thirty to one hundred and twenty activities per problem instance, show that the algorithm scales well and is competitive with other exact solution approaches. The computational results show that the most difficult problems occur when scarce resource supply and the structure of the resource demand cause a problem to be highly disjunctive.