As a means to obtain a more accurate description of traffic flows than that provided by the basic model of traffic assignment, there have been suggestions to impose upper bounds on the link flows. This can be done either by introducing explicit link capacities or by employing travel time functions with asymptotes at the upper bounds. Although the latter alternative has the disadvantage of inherent numerical ill-conditioning, the capacitated assignment model has been studied and applied to a limited extent, the main reason being that the solutions can not be characterized by the classical Wardrop equilibrium conditions; they may, however, be characterized as Wardrop equilibria in terms of a welldefined, natural generalized travel cost.

The class of simplicial decomposition (SD) schemes have shown to provide efficient tools for nonlinear network flows. When applied to the traffic assignment problem, shortest route subproblems are solved in order to generate extreme points of the polyhedron of feasible flows, and, alternately, master problems are solved over the convex hull of the generated extreme points. We review the development of simplicial decomposition and the closely related column generation methods for the traffic assignment problem; we then present a modified, disaggregated, representation of feasible solutions in SD algorithms for convex problems over Cartesian product sets, with application to the symmetric traffic assignment problem. The new algorithm, which is referred to as disaggregate simplicial decomposition (DSD), is given along with a specialized solution method for the disaggregate master problem. Numerical results for several well known test problems and a new one are presented. These experimentations indicate that only few shortest route searches are needed; this property is important for large-scale applications. The modification proposed maintains the advantages of SD, and the results show that the performance of the new algorithm is at least comparable to that of state-of-the-art codes for traffic assignment. Moreover, the reoptimization capabilities of the new scheme are significantly better; this is a main motive for considering it. The reoptimization facilities, especially with respect to changes in origin-destination flows and network topology, make the new approach highly profitable for more complex models, where traffic assignment problems arise as subproblems.

Lagrangean dualization and subgradient optimization techniques are frequently used within the eld of computational optimization for nding approximate solutions to large, structured optimization problems. The dual subgradient scheme does not automatically produce primal feasible solutions; there is an abundance of techniques for computing such solutions (via penalty functions, tangential approximation schemes, or the solution of auxiliary primal programs), all of which require a fair amount of computational e ort.We consider a subgradient optimization scheme applied to a Lagrangean dual formulation of a convex program, and construct, at minor cost, an ergodic sequence of subproblem solutions which converges to the primal solution set. Numerical experiments performed on a tra c equilibrium assignment problem under road pricing show that the computation of the ergodic sequence results in a considerable improvement in the quality of the primal solutions obtained, compared to those generated in the basic subgradient scheme.

We consider the introduction of side constraints for refining a descriptive or prescriptive traffic equilibrium assignment model, and analyze a general such a model. Side constraints can be introduced for several diverse reasons; we consider three basic ones. First, they can be used to describe the effects of a traffic control policy. Second, they can be used to improve an existing traffic equilibrium model for a given application by introducing, through them, further information about the traffic flow situation at hand. As such, these two strategies complement the refinement strategy based on the use of non-separable, and typically asymmetric, travel cost functions. Third, they can be used to describe flow restrictions that a central authority wishes to impose upon the users of the network. We study a general convexly side constrained traffic equilibrium assignment model, and establish several results pertaining to the above described areas of application. First, for the case of prescriptive side constraints that are associated with queueing effects, for example those describing signal controls, we establish a characterization of the solutions to the model through a Wardrop user equilibrium principle in terms of generalized travel costs and an equilibrium queueing delay result; in traffic networks with queueing the solutions may therefore be characterized as Wardrop equilibria in terms of well-defined and natural travel costs. Second, we show that the side constrained problem is equivalent to an equilibrium model with travel cost functions properly adjusted to take into account the information introduced through the side constraints. Third, we show that the introduction of side constraints can be used as a means to derive the link tolls that should be levied in order to achieve a set of traffic management goals. The introduction of side constraints makes the problem computationally more demanding, but this drawback can to some extent be overcome through the use of dualization approaches, which we also briefly discuss.

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Hospital wards need to be staffed by nurses round the clock, resulting in irregular working hours for many nurses. Over the years, the nurses' influence on the scheduling has been increased in order to improve their working conditions. In Sweden it is common to apply a kind of self-scheduling where each nurse individually proposes a schedule, and then the final schedule is determined through informal negotiations between the nurses. This kind of self-scheduling is very time-consuming and does often lead to conflicts.We present a pilot study which aims at determining if it is possible to create an optimisation tool that automatically delivers a usable schedule based on the schedules proposed by the nurses. The study is performed at a typical Swedish nursing ward, for which we have developed a mathematical model and delivered schedules. The results of this study are very promising.

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