Look-ahead heuristics for the dynamic traveling purchaser problem

  • Authors:

  • Enrico Angelelli;Renata Mansini;Michele Vindigni

  • Affiliations:

  • Department of Quantitative Methods, University of Brescia, Italy;Department of Information Engineering, University of Brescia, Italy;Department of Quantitative Methods, University of Brescia, Italy

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2011

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Abstract

Given a set of products each with positive discrete demand, and a set of markets selling products at given prices, the traveling purchaser problem (TPP) looks for a tour visiting a subset of markets such that products demand is satisfied at minimum purchasing and traveling costs. In this paper we analyze a dynamic variant of the problem, where quantities may decrease as time goes on. Complete information is assumed on current state of the world, i.e.decision maker knows quantities available for each product in each market at present time and is informed about any consumption event when it occurs. Nevertheless, planner does not have any information on future events. Two groups of heuristics are described and compared. The first group consists of simplified approaches deciding which market to visit next on the basis of some greedy criteria considering only one of the two objective costs. The second one includes heuristics based on a look-ahead approach taking into account both traveling and purchasing costs and inserting some future prediction. Heuristics behavior has been tested on a large set of randomly generated instances under different levels of dynamism.