Optimizing resource recharging location-routing plans: A resource-space-time network modeling framework for railway locomotive refueling applications

Gongyuan Lu, Xuesong Zhou, Monirehalsadat Mahmoudi, Tie Shi, Qiyuan Peng

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The resource recharging location-routing problem is a generalization of the location routing problem with sophisticated and critical resource consumption and recharging constraints. Based on a representation of discretized acyclic resource-space-time networks, we propose a generic formulation to optimize dynamic infrastructure location and routes decisions, with a special focus on railway locomotive routing and refueling problems. The proposed integer linear programming formulation could greatly simplify the modeling representation of time window, resource change, and sub-tour constraints through a well-structured multi-dimensional network. An approximation solution framework based on the Lagrangian relaxation is developed to decompose the problem to a knapsack sub-problem for selecting recharging stations and a vehicle routing sub-problem in a space-time network. Both sub-problems can be solved through dynamic programming algorithms to obtain optimal solution. A number of experiments are used to demonstrate the Lagrangian multiplier adjustment-based location routing decision making, as well as the effectiveness of the developed algorithm in large-scale networks.

Original languageEnglish (US)
JournalComputers and Industrial Engineering
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Locomotives
Vehicle routing
Dynamic programming
Linear programming
Decision making
Experiments

Keywords

  • Lagrangian relaxation
  • Location routing
  • Railway Management
  • Resource-space-time network
  • Vehicle routing problem with recharging station

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

Optimizing resource recharging location-routing plans : A resource-space-time network modeling framework for railway locomotive refueling applications. / Lu, Gongyuan; Zhou, Xuesong; Mahmoudi, Monirehalsadat; Shi, Tie; Peng, Qiyuan.

In: Computers and Industrial Engineering, 01.01.2018.

Research output: Contribution to journalArticle

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