A metaheuristic for the multimodal network flow problem with product quality preservation and empty repositioning

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2 Citations (Scopus)

Abstract

We study a transportation planning problem with multiple transportation modes, perishable products, and management of Reusable Transport Items (RTIs). This problem is inspired by the European horticultural chain. We present a Mixed Integer Programming (MIP) optimization model which is an extension of the Fixed-charge Capacitated Multicommodity Network Flow Problem (FCMNFP). The MIP integrates dynamic allocation, flow, and repositioning of the RTIs in order to find the trade-off between product freshness requirements, and operational circumstances and costs. We furthermore propose an Adaptive Large Neighborhood Search (ALNS) algorithm with new neighborhoods, and intensification and diversification strategies. We then provide detailed computational analysis on its properties, compare its results with a state-of-the-art MIP solver, and provide practical insights.

LanguageEnglish
Pages321-344
JournalTransportation Research Part B: Methodological
Volume106
DOIs
StatePublished - 2017

Fingerprint

Integer programming
programming
optimization model
diversification
Planning
planning
costs
management
Metaheuristics
Network flow
Mixed integer programming
Product quality
Costs

Keywords

  • Adaptive Large Neighborhood Search (ANLS)
  • Mixed Integer Programming (MIP)
  • Multimodal transportation
  • Perishability
  • Reusable transport item

Cite this

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title = "A metaheuristic for the multimodal network flow problem with product quality preservation and empty repositioning",
abstract = "We study a transportation planning problem with multiple transportation modes, perishable products, and management of Reusable Transport Items (RTIs). This problem is inspired by the European horticultural chain. We present a Mixed Integer Programming (MIP) optimization model which is an extension of the Fixed-charge Capacitated Multicommodity Network Flow Problem (FCMNFP). The MIP integrates dynamic allocation, flow, and repositioning of the RTIs in order to find the trade-off between product freshness requirements, and operational circumstances and costs. We furthermore propose an Adaptive Large Neighborhood Search (ALNS) algorithm with new neighborhoods, and intensification and diversification strategies. We then provide detailed computational analysis on its properties, compare its results with a state-of-the-art MIP solver, and provide practical insights.",
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AU - Dellaert,N.P.

AU - Nuijten,W.

AU - van Woensel,T.

PY - 2017

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