大同御河兴云桥的历史及建筑形制

御河是大同市内最主要的一条河流，它由北而南从城东门外流过。作为东出必经之路，御河桥上建置桥梁有着悠久的历史。目前，根据考古出土文物及参考文献可以得知，御河上建桥有确切记载始于金代，它是一座五拱石桥，元代重修时命名“兴云桥”。金代御河桥经元明二代历时四百余年，万历八年拓故基重建为十九孔石拱桥，‘仍名兴云桥，清嘉庆年间倾圯。     

Environmental taxation and the double dividend hypothesis in CGE modelling literature: A critical review

Computable general equilibrium (CGE) modelling is a flexible and open way to model the economic systems that allow practitioners to assess the impacts of different policies or external shocks over an economic system. There is some empirical literature dedicated to test the double dividend hypothesis of an environmental tax reform using CGE models. This hypothesis claims that is possible to obtain an improvement of both environmental and economic conditions by imposing an environmental tax and recycling revenues obtained to reduce other pre-existing taxes. This research provides a comprehensive review of this literature including a statistical and a meta-regression analysis. 69 different simulations from 40 studies have been analyzed. 55% of simulations have achieved a double dividend, concluding that although the environmental dividend is almost always achieved, the economic dividend still remains an ambiguous question that needs further research.     

An agent-based approach to modelling virtual enterprises

This paper describes how virtual enterprises (VEs) can be modelled using the AGORA multi-agent architecture, designed for modelling and supporting cooperative work among distributed entities. The model consists of a structure of AGORAs and agents, where AGORAs are facilitators of cooperative work for agents and the agents represent the partners of the VE, the cooperative mechanisms and the service providers. The distributed and goal-oriented nature of the VE provides a strong motivation for the use of agents to model VEs. The main advantages of this approach are that the structure of AGORAs provides a homogeneous modelling environment throughout the life cycle of the VE, traceability of the VE activities and a history of the VE. In addition to these, it is important to point out that, agents being computational entities, the resulting model provides an easy and efficient passage from the model to the computational support that is required by the VE.     

Models for supply chain reengineering

The goal of this paper is to provide a first step in the development of a coherent set of modelling methods for supply chain reengineering. This paper shows that different fields of attention in supply chain management should be approached with different modelling methods. Three modelling methods are presented: the event process chain (EPC) method; the activity chain model (ACM) method; and the GRAI grid method (adjusted for supply chains). EPC modelling focuses on time relationships between primary processes/functions, and is customer oriented. ACM modelling focuses on functions/processes and information flows. GRAI focuses on decision structures and information flows. The three methods are described, and an application of the methods to a case study company is presented. This paper concludes with a comparison of the methods and a discussion of their applicability.     

Telecommunications Network Design—Comparison of Alternative Approaches

The design and development of the network infrastructure to support mission‐critical applications has become a critical and‐complex activity. This study explores the use of genetic algorithms (GA) for network design in the context of degree‐constrained minimal spanning tree (DCMST) problem; compares for small networks the performance of GA with a mathematical model that provides optimal solutions; and for larger networks, compares GA's performance with two heuristic methods—edge exchange and primal algorithm. Two performance measures, solution quality and computation time, are used for evaluation. The algorithms are evaluated on a wide variety of network sizes with both static and dynamic degree constraints on the network nodes. The results indicate that GA provides optimal solutions for small networks. For larger networks it provides better solution quality compared to edge exchange and primal method, but is worse than the two methods in computation time.