A template-based Tabu Search algorithm for the Consistent Vehicle Routing Problem

  • Authors:

  • C. D. Tarantilis;F. Stavropoulou;P. P. Repoussis

  • Affiliations:

  • Center for Operations Research & Decision Systems, Management Science Laboratory, Department of Management Science & Technology, Athens University of Economics & Business, Athens, Greece;Center for Operations Research & Decision Systems, Management Science Laboratory, Department of Management Science & Technology, Athens University of Economics & Business, Athens, Greece;Center for Operations Research & Decision Systems, Management Science Laboratory, Department of Management Science & Technology, Athens University of Economics & Business, Athens, Greece

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

This paper presents a generic template-based solution framework and its application to the so-called Consistent Vehicle Routing Problem (ConVRP). The ConVRP is an NP-hard combinatorial optimization problem and involves the design of a set of minimum cost vehicle routes to service a set of customers with known demands over multiple days. Customers may receive service either once or with a predefined frequency; however frequent customers must receive consistent service, i.e., must be visited by the same driver over approximately the same time throughout the planning period. The proposed solution framework adopts a two-level master-slave decomposition scheme. Initially, a master template route schedule is constructed in an effort to determine the service sequence and assignment of frequent customers to vehicles. On return, the master template is used as the basis to design the actual vehicle routes and service schedules for both frequent and non-frequent customers over multiple days. To this end, a Tabu Search improvement method is employed that operates on a dual mode basis and modifies both the template routes and the actual daily schedules in a sequential fashion. Computational experiments on benchmark data sets illustrate the competitiveness of the proposed approach compared to existing results.