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<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">Among the techniques supporting a multidecision context, as a supply chain is, distribution simulation can undoubtedly play an important role in a co-operative environment. The distribution simulation for supply chain has its advantages to find and solve bottleneck of supply chain. Considering the design of distribution simulation platform for supply chain, the realization of time synchronization and time advance will be the key points. This paper proposes an advancing mechanism that integrates High Level Architecture with multi-agent distributed simulation to meet time management in supply chain simulation, i.e., a ’heterogeneous’ system is built during our research. We present some preliminary experimental results which illustrate the performance of our advancing mechanism on our platform established. Finally, the experimental results have demonstrated the novel time advancing mechanism can be successfully applied in supply chain contexts, and surely prove that it is feasible and scientific. <em></em></span></span></p>

The U.S. Environmental Protection Agency has released a new generation regulatory mobile emission model, called MOVES (motor vehicle emission simulator), to replace its current emission models, MOBILE and NONROAD. On its formal adoption, MOVES will have important implications for regional mobile emission inventories, particularly concerning transportation conformity to the 1990 Clean Air Act Amendment. MOVES will not only improve emissions inventory estimates, but it will also expand the capabilities to perform quantitative project-level emission inventories that are not possible with the latest version of MOBILE. MOVES is designed to estimate emissions at scales ranging from individual roads and intersections to county-, region-, and nationwide. The first objective of this paper is to provide a comprehensive documentation of the differences between MOVES and MOBILE in terms of model methodology, scope, and features. The second objective is to fill the void in the literature on the comparison of MOVES and MOBILE at the regional level through a real-world case study. Using Cook County in Illinois, the authors compared emission estimates of carbon dioxide and nitrogen oxides in the latest versions of both models. For this purpose, consistent local specific input data are incorporated into the models. The third objective is to provide insights on input data requirements for MOVES to practitioners and metropolitan planning organizations to facilitate their transition from MOBILE to MOVES in the near future.

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