The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach

Hu Qin, Anton Moriakin, Gangyan Xu, Jiliu Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Motivated by the need for uninterrupted service provision in the telecommunications industry, this paper presents a novel problem concerning the transportation of diesel generators during an unplanned power outage. Given a set of base stations, each equipped with a capacitated back-up battery pack, the problem consists in finding an optimal delivery and pick-up schedule that minimises corresponding costs. The problem is significantly complicated by the fact that the delivery quantity is a decision variable, and the pick-up times depend on the delivery time, delivery quantity and constraints related to battery-charging requirements. To address the issue, we develop problem-specific pick-up time functions that can be effectively incorporated into the proposed algorithm. The problem is formulated as an arc-based model and a set-packing model. To solve it to optimality, we design a tailored branch-and-price-and-cut algorithm, including novel customised dominance criteria in the labelling algorithm and adopting heuristics that exploit the problem features and effectively improve the algorithmic performance. The efficacy of the proposed algorithm is validated based on the extensive computational study and compared with a commercial solver. The proposed acceleration techniques are found to be potent with regard to computational times, and useful managerial insights are provided as part of sensitivity analyses.

Original languageEnglish
JournalEuropean Journal of Operational Research
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Battery-charging constraints
  • Pick-up and delivery
  • Power outage
  • Time functions
  • Transportation

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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