Traditionally, optimization of diamond interchange timings has been done with PASSER III for standard and special diamond phasing sequences. PASSER III is limited because it is designed for undersaturated conditions. It applies vertical stacking of queues and is not capable of modeling queue spillback conditions in its current form. This deficiency is addressed by the arterial signal coordination software (ASCS), whose capabilities in timing diamond interchanges in under-saturated and oversaturated conditions are presented here. ASCS consists of three modules: ( a) input module, a user interface through which volume and geometry inputs can be provided to the program; ( b) optimization module, a genetic algorithm-based optimization routine that can optimize signal timings; and ( c) analysis module, which consists of a bandwidth analysis routine and a delay analysis routine (DAR). The DAR is a mesoscopic simulator that applies a second-by-second analysis of flows for modeling flows accurately. DAR applies horizontal stacking of queues and shock wave analysis to estimate the performance of traffic operations. Validation of ASCS for oversaturated arterial links against PASSER III and CORSIM was conducted. The results indicate that delay and throughput estimation in ASCS are realistic. The genetic algorithm-based optimization routine in ASCS was applied to estimate diamond interchange timings for three scenarios. Where queue spillback occurred, ASCS clearly outperformed PASSER III. ASCS produced near-optimal results for all scenarios studied.
The objective of this study was to develop a methodology for assessing the impact of road construction that could be used to (a) predict the network-level impact of road construction projects, (b) identify critical roadway segments and corridors in which the impacts of construction are expected to be the most severe, and (c) compare alternative construction scenarios and schedules. Dynamic traffic assignment formed the basis of an approach to assess the regional impact of road construction and compare alternative construction schedule scenarios. The application of the model was illustrated with the use of a hypothetical case of two road construction projects in the roadway system of El Paso, Texas.
The manager is responsible for the operations of a distribution center (DC) and multiple retail outlets selling a seasonal product. Initially, the DC keeps the inventory, which is allocated to the outlets in the season. There are inventory holding costs at the DC and the outlets; variable shipment cost for transferring inventory from the DC; fixed ordering cost and shortage cost at an outlet. Exact demand at each outlet is a decreasing function of price. To maximize the expected profit of the season, the manager needs to determine the markdown prices for retail outlets and quantity of inventory allocated to them. The problem can be modeled as a dynamic program (DP) which takes too heavy computational effort to solve. We develop a DP-based heuristic for solving the problem. The heuristic takes light computational effort and yet has good accuracy. Insights streamlining the markdown operations are deduced from the numerical results.
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