Liner shipping network design with sensitive demand

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

Fersiynau electronig

Dangosydd eitem ddigidol (DOI)

  • Ali Cheaitou
    University of Sharjah
  • Sadeque Hamdan
    Université Paris-Saclay
  • Rim Larbi
    University of Carthage, Tunis

Purpose

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.
Design/methodology/approach

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.
Findings

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.
Research limitations/implications

The vessel carrying capacity is not considered in an explicit way.
Originality/value

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.
Iaith wreiddiolSaesneg
Tudalennau (o-i)293-313
CyfnodolynMaritime Business Review
Cyfrol6
Rhif y cyfnodolyn3
Dyddiad ar-lein cynnar1 Chwef 2021
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 6 Medi 2021
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