An integrated fleet planning model with empty vehicle repositioning for an intermodal transportation system


OPERATIONAL RESEARCH, vol.22, no.3, pp.2063-2098, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.1007/s12351-021-00642-5
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.2063-2098
  • Keywords: Intermodal transportation, Freight planning, Empty vehicle repositioning, Fleet allocation, Fleet composition, Mixed integer programming, FREIGHT TRANSPORT, CONTAINER FLEET, NETWORK DESIGN, ASSIGNMENT MODEL, OPTIMIZATION, SIZE, SERVICE, MANAGEMENT, STRATEGY, DECISION
  • Dokuz Eylül University Affiliated: Yes


Fleet planning problems in intermodal transportation represent one of the most important problems in logistics. In addition to the integration of various sub-problems interrelated at different planning levels, i.e., strategic, tactical, and operational, the inclusion of multiple modes, resources, and multiple actors in intermodal transportation systems makes fleet planning more complex in comparison with unimodal systems. The present paper proposes a holistic fleet planning approach, which integrates various decisions such as freight planning (transport mode, service type and route selection), fleet composition and allocation, empty vehicle repositions, fleet expansion/reduction and outsourcing. A comprehensive mixed-integer linear programming (MILP) model is developed for an international logistics company, which operates a large intermodal network in Europe. The computational results of the case study have shown that application of a reallocation strategy may provide cost reduction up to 10% for the logistics company. Considering the existing situation of the company, outsourcing can be reduced up to 30%, and fleet utilization can be increased by 5% by applying the proposed model. The extensive case study also shows that effective and efficient fleet plans can be generated through the proposed MILP model.