nep-cmp New Economics Papers
on Computational Economics
Issue of 2006‒12‒09
four papers chosen by
Stan Miles
Thompson Rivers University

  1. Wavelet Applications to Heterogeneous Agents Model By Lukáš Vácha; Miloslav Vošvrda
  2. Heterogeneous Agents Model with the Worst Out Algorithm By Lukáš Vácha; Miloslav Vošvrda
  3. Supply Chain Optimization in Pulp Distribution using a Rolling Horizon Solution Approach By Bredström, David; Rönnqvist, Mikael
  4. Combined vehicle routing and scheduling with temporal precedence and synchronization constraints By Bredström, David; Rönnqvist, Mikael

  1. By: Lukáš Vácha (Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic); Miloslav Vošvrda (Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic; Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic)
    Abstract: A heterogeneous agent model with the WOA was considered for obtaining more realistic market conditions. The WOA replaces periodically the trading strategies that have the lowest performance level of all strategies presented on the market by the new ones. New strategies that enter on the market have the same stochastic structure as an initial set of strategies. This paper shows, by wavelets applications, strata influences of the trading strategies with the WOA.
    Keywords: agents’ trading strategies; heterogeneous agent model with stochastic memory; worst out algorithm; wavelet
    JEL: C61 G14 D84
    Date: 2006–04
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2006_21&r=cmp
  2. By: Lukáš Vácha (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic; Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic); Miloslav Vošvrda (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic; Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic)
    Abstract: Heterogeneous agents' model with the stochastic beliefs formation is considered. Fundamentalists rely on their model employing fundamental information basis to forecast the next price period. Chartists determine whether current conditions call for the acquisition of fundamental information in a forward looking manner rather than relying on the past performance. It was shown that implementation of the agents memory can significantly change the preferences of trader strategies. The Worst out Algorithm (WOA) is used with considered heterogeneous agents’ model to simulate more realistic market conditions. The WOA replaces periodically the trading strategy that has the lowest performance level of all strategies presented on the market by the new one. The memory length of the new strategy that enters the market has the same stochastic structure as the initial strategies. This paper shows an influence of the agent memory as a stochastic process on the heterogeneous agents model with the WOA. Simulations show difference in price returns behaviour between two types of agents’ memory length distribution functions (Uniform and Normal). There is a significant difference in the values of the Hurst exponent and the variance in these two cases. A lower Hurst exponent in the uniform case is caused by a richer spectrum of agents’ memory length, because agents are equally distributed across all trading horizons. For the uniform case there is no opportunity for any prediction. On the other hand, the value of the Hurst exponent gives a signal for a possibility of the price prediction in the normal case.
    Keywords: Efficient Markets Hypothesis; Fractal Market Hypothesis; agents' investment horizons; agents' trading strategies; technical trading rules; heterogeneous agent model with stochastic memory; Worst out Algorithm
    JEL: C61 G14 D84
    Date: 2005
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp091&r=cmp
  3. By: Bredström, David (Dept. of Mathematics, Linköpings universitet); Rönnqvist, Mikael (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)
    Abstract: In this paper we consider a combined supply chain and ship routing problem for a large pulp producer in Scandinavia. The problem concerns the distribution of pulp to customers, with route scheduling of ships as a central part of modeling. It is an operative planning problem with daily ship routing decisions over a 40 days period. The pulp supply is determined by fixed production plans, and the transport flows and storages are modeled with the requirement to satisfy the demand in a cost-optimal way. We develop a mixed integer programming model with binary variables for route usage of a vessel. The problem is solved with a heuristic solution method, based on a rolling time horizon and a standard branch and bound algorithm. We apply the heuristic on problem instances with real world data, and compare results from reduced problem instances with the results from an exact branch and bound search. The computational experiments indicate that real world problems are solvable with the solution method and that it in many cases can be very efficient.
    Keywords: Supply chain; Ships; Scheduling; Mixed integer programming
    JEL: Q21
    Date: 2006–12–01
    URL: http://d.repec.org/n?u=RePEc:hhs:nhhfms:2006_017&r=cmp
  4. By: Bredström, David (Dept. of Mathematics, Linköpings universitet); Rönnqvist, Mikael (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)
    Abstract: We present a mathematical programming model for the combined vehicle routing and scheduling problem with time windows and additional temporal constraints. The temporal constraints allow for imposing pairwise synchronization and pairwise temporal precedence between customer visits, independently of the vehicles. We describe some real world problems where the temporal constraints, in the literature, usually are remarkably simplified in the solution process, even though these constraints may significantly improve the solution quality and/or usability. We also propose an optimization based heuristic to solve real size instances. The results of numerical experiments substantiate the importance of the temporal constraints in the solution approach. We also make a computational study by comparing a direct usage of a commercial solver against the proposed heuristic where the latter approach can find high quality solutions within distinct time limits.
    Keywords: Routing; Scheduling; Temporal Constraints; Synchronization; Branch and Bound
    JEL: C61
    Date: 2006–12–01
    URL: http://d.repec.org/n?u=RePEc:hhs:nhhfms:2006_018&r=cmp

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