Combining mesoscopic and microscopic simulation in an integrated environment as a hybrid solution

The evaluation of advanced Intelligent Transportation Systems, and particularly those which involve real–time traffic management, requires a network-wide assessment of their impact as opposed to an isolated analysis of key intersections. To support such assessments, an integrated simulation environment that allows the use of different modeling levels (e.g., macro-meso-micro) offers undeniable advantages. One of the advantages is that traffic assignment results produced by any type of network loading modeling can be stored and reused for another simulation run. But even in an integrated environment with separate models, deciding between microscopic or mesoscopic was until recently a necessary and difficult choice. On the one hand, microscopic traffic simulation models emulate the dynamics of individual vehicles in a detailed network representation based on car-following, lane changing, and gap acceptance models. They also account explicitly for traffic control. As such, they are very appropriate for operational analysis due to the detail of information provided by the simulator. However, they have a significant calibration and computational cost. On the other hand, mesoscopic models combine simplified flow dynamics with explicit treatment of interrupted flows at intersections and allow modeling of large networks with high computational efficiency. However, the loss of realism implied by a mesoscopic model makes it necessary to emulate detailed outputs; for instance, de-tector measurements or instantaneous emissions. Some outputs, such as the number of start-stops or the exact location of con-gestion within a section elude even the most detailed mesoscopic simulators. This analysis gives rise to the need to combine meso and micro approaches into new concurrent hybrid traffic simulators where very large-scale networks are modeled mesoscopically and areas of complex interactions benefit from the finer detail of microscopic simulation. Combining an event-based mesoscopic model with a more detailed, time-sliced microsimulator raises consistency problems within the network rep-resentation and the meso-micro-meso transitions

Scheduling the production of two-component jobs on a single machine

In this paper, we examine the scheduling of jobs, each of which comprises a standard and a specific component, on a single machine. A set-up time is required before each batch of standard components is processed. A job is completed when both its standard and specific components have been processed and are available. Standard components only become available when the batch to which they belong is completed, whereas specific components are available on completion of their processing. We present results for two well-known due-date related criteria. In particular, an O(n2) dynamic programming algorithm is derived for the problem of minimising the maximum lateness. For minimising the number of late jobs, we show that the problem is NP-hard and give a dynamic programming algorithm that requires pseudo-polynomial time. Finally, we show that a variant of the number of late jobs problem, in which there is a common processing time for the standard components, is solvable in O(n4 log n) time