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The accessibility arc upgrading problem

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  • Maya Duque, Pablo A.
  • Coene, Sofie
  • Goos, Peter
  • Sörensen, Kenneth
  • Spieksma, Frits

Abstract

The accessibility arc upgrading problem (AAUP) is a network upgrading problem that arises in real-life decision processes such as rural network planning. In this paper, we propose a linear integer programming formulation and two solution approaches for this problem. The first approach is based on the knapsack problem and uses the knowledge gathered from an analytical study of some special cases of the AAUP. The second approach is a variable neighbourhood search with strategic oscillation. The excellent performance of both approaches is demonstrated using a large set of randomly generated instances. Finally, we stress the importance of a proper allocation of scarce resources in accessibility improvement.

Suggested Citation

  • Maya Duque, Pablo A. & Coene, Sofie & Goos, Peter & Sörensen, Kenneth & Spieksma, Frits, 2013. "The accessibility arc upgrading problem," European Journal of Operational Research, Elsevier, vol. 224(3), pages 458-465.
    • Handle: RePEc:eee:ejores:v:224:y:2013:i:3:p:458-465
    DOI: 10.1016/j.ejor.2012.09.005
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    1. Murawski, Lisa & Church, Richard L., 2009. "Improving accessibility to rural health services: The maximal covering network improvement problem," Socio-Economic Planning Sciences, Elsevier, vol. 43(2), pages 102-110, June.
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    Cited by:

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    2. Yücel, E. & Salman, F.S. & Arsik, I., 2018. "Improving post-disaster road network accessibility by strengthening links against failures," European Journal of Operational Research, Elsevier, vol. 269(2), pages 406-422.
    3. Maya Duque, Pablo A. & Dolinskaya, Irina S. & Sörensen, Kenneth, 2016. "Network repair crew scheduling and routing for emergency relief distribution problem," European Journal of Operational Research, Elsevier, vol. 248(1), pages 272-285.
    4. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    5. Michael Holzhauser & Sven O. Krumke & Clemens Thielen, 2016. "Budget-constrained minimum cost flows," Journal of Combinatorial Optimization, Springer, vol. 31(4), pages 1720-1745, May.
    6. Lazar Mrkela & Zorica Stanimirović, 2022. "A variable neighborhood search for the budget-constrained maximal covering location problem with customer preference ordering," Operational Research, Springer, vol. 22(5), pages 5913-5951, November.

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