In this paper we deal with the problem of finding the first K shortest paths from a single origin node to all other nodes of a directed graph. In particular, we define the necessary and sufficient conditions for a set of distance label vectors, on the basis of which we propose a class of methods which can be viewed as an extension of the generic label-correcting method for solving the classical single-origin all-destinations shortest path problem. The data structure used is characterized by a set of K lists of candidate nodes, and the proposed methods differ in the strategy used to select the node to be extracted at each iteration. The computational results show that: 1. some label-correcting methods are generally much faster than the double sweep method of Shier (1979); 2. the most efficient node selection strategies, used for solving the classical single-origin all-destinations shortest path problem, have proved to be effective also in the case of the K shortest paths.
In this paper we propose an artificial market where multiple risky assets are exchanged. Agents are constrained by the availability of resources and trade to adjust their portfolio according to an exogenously given target portfolio. We model the trading mechanism as a continuous auction order-driven market. Agents are heterogeneous in terms of desired target portfolio allocations, but they are homogeneous in terms of trading strategies. We investigate the role played by the trading mechanism in affecting the dynamics of prices, trading volume and volatility. We show that the institutional setting of a double auction market is sufficient to generate a non-normal distribution of price changes and temporal patterns that resemble those observed in real markets. Moreover, we highlight the role played by the interaction between individual wealth constraints and the market frictions associated with a double auction system to determine the negative asymmetry of the stock returns distribution.
PrefaceWith the advent of rising mobility and leisure time together with a structural tendency for declining airfares, tourism has become a sector of major significance in modern economies. There is a wealth of literature on the motives of tourists, on the sustainability aspects of large-scale tourism, on the expected economic and social consequences of tourism in host countries and regions, on the attractiveness of different localities and tourist sites (e.g., beaches, historico-cultural heritage, nature etc.), or on local or regional initiatives to promote tourism (e.g., through tourism packages, e-services etc.). Tourism research has indeed become a booming and timely research approach in contemporaneous economics.There is indeed a host of descriptive, qualitative and policy-oriented research, but applied and quantitatively-oriented economic research is still underrepresented. Fortunately, we have witnessed in the past years an upsurge of model-based economic research in the tourist sector, which builds on powerful research tools in quantitative economics, such as discrete choice models, social accounting matrices, data envelopment analysis, impact assessment models or partial computable equilibrium models including environmental externalities. The present volume originates from this novel research spirit in tourism economics and aims to offer an attractive collection of operational research tools and approaches in tourism research. Originality and advanced methodology have been the major criteria for selecting these contributions. They form an appealing record of modern tourism economic research and position tourism economics within the strong tradition of quantitative economic research, with due attention for both the demand and supply side of the tourism sector, including technological and logistic advances in the sector. This volume offers thus examples of pioneering research in tourism economics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.