Preface

Preface

Preface     

Integrated modelling and numerical treatment of freeway flow

The effectiveness of macroscopic dynamic freeway flow models at both uninterrupted and interrupted flow conditions is tested. Model implementation is made by finite difference methods developed here for solving the system's governing equations. These schemes are more effective than existing numerical methods, particularly when generation terms are introduced. The modelling alternatives and numerical solution algorithms are compared by employing a data base generated through microscopic simulation. Despite the effectiveness of the proposed numerical treatments, substantial deviations from the data at interrupted flows are still noticeable. In order to improve performance when flow is interrupted, we develop a modelling methodology that takes into account the ramp-freeway interactions so that all freeway components are treated as a system. We show that the coupling effects of the merging traffic streams are significant. Finally, the incremental benefits of using the more sophisticated high-order continuum models are assessed.     

Efficiency Conditions and Duality for a Class of Multiobjective Fractional Programming Problems

A class of constrained multiobjective fractional programming problems is considered from a viewpoint of the generalized convexity. Some basic concepts about the generalized convexity of functions, including a unified formulation of generalized convexity, are presented. Based upon the concept of the generalized convexity, efficiency conditions and duality for a class of multiobjective fractional programming problems are obtained. For three types of duals of the multiobjective fractional programming problem, the corresponding duality theorems are also established.     

The harmonic oscillator energy level spacing for neutrons and protons in nuclei

Approximate expressions of?ω for neutrons and protons separately, as functions of the neutron numberN and the proton numberZ respectively, are derived. The dependence ?ω_n(?ω_p) on N(Z) is established using a rather recently proposed semi-phenomenological density distribution based on the separation energies of the last neutron or proton. The corresponding curves of?ω show “discontinuities in the slope” at the closed shells throughout the periodic table. The difference ?ω_n — {ie17-01} is also discussed.     

Dynamics of energy transport in ternary molecular solids. II. Time evolution of naphthalene fluorescence

The spectrally resolved time-evolution of free and trapped singlet excitons was obtained at liquid-helium temperature for ternary crystals of perdeuteronaphthalene/naphthalene/betamethylnaphthalene (host/guest/supertrap). The naphthalene guest (donor) concentration varied between 0.30 and 0.99 mole fraction, while the supertrap (acceptor) concentrations were 10^?4–10^?5. At the lower guest concentrations (0.50 and below) the naphthalene-exciton decay time approaches the natural lifetime (≈ 122 ns). At higher concentrations, the decay is much shorter and extremely non-exponential. This behavior is inconsistent with simple homogeneous kinetics schemes that use a time-independent rate constant for energy transport. Above the percolation concentration (0.60 naphthalene) we fitted the experimental results with a random-flight-kinetic model, incorporating correlated random walks on the percolating guest cluster. The best fit was obtained for a “coherence length” (mean free path) of ≈ 10² lattice units. These results are in good agreement with previous steady-state studies on the same samples, and seem to indicate a partial coherence of the exciton transport in both pure and substitutionally disordered crystals at these low temperatures.     

Parallel computing in nonconvex programming

In this paper, we are concerned with the development of parallel algorithms for solving some classes of nonconvex optimization problems. We present an introductory survey of parallel algorithms that have been used to solve structured problems (partially separable, and large-scale block structured problems), and algorithms based on parallel local searches for solving general nonconvex problems. Indefinite quadratic programming posynomial optimization, and the general global concave minimization problem can be solved using these approaches. In addition, for the minimum concave cost network flow problem, we are going to present new parallel search algorithms for large-scale problems. Computational results of an efficient implementation on a multi-transputer system will be presented.     

Asymptotic Results for Random Multidimensional Assignment Problems

The multidimensional assignment problem (MAP) is an NP-hard combinatorial optimization problem occurring in applications such as data association and target tracking. In this paper, we investigate characteristics of the mean optimal solution values for random MAPs with axial constraints. Throughout the study, we consider cost coefficients taken from three different random distributions: uniform, exponential and standard normal. In the cases of uniform and exponential costs, experimental data indicates that the mean optimal value converges to zero when the problem size increases. We give a short proof of this result for the case of exponentially distributed costs when the number of elements in each dimension is restricted to two. In the case of standard normal costs, experimental data indicates the mean optimal value goes to negative infinity with increasing problem size. Using curve fitting techniques, we develop numerical estimates of the mean optimal value for various sized problems. The experiments indicate that numerical estimates are quite accurate in predicting the optimal solution value of a random instance of the MAP.     

Filled functions for unconstrained global optimization

This paper is concerned with filled function techniques for unconstrained global minimization of a continuous function of several variables. More general forms of filled functions are presented for smooth and non-smooth optimization problems. These functions have either one or two adjustable parameters. Conditions on functions and on the values of parameters are given so that the constructed functions have the desired properties of filled functions.