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Solving Transport Infrastructure Investment Project Selection and Scheduling Using Genetic Algorithms

Author

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  • Karel Ječmen

    (Department of Air Transport, Czech Technical University in Prague, 128 03 Prague, Czech Republic)

  • Denisa Mocková

    (Department of Air Transport, Czech Technical University in Prague, 128 03 Prague, Czech Republic)

  • Dušan Teichmann

    (Department of Air Transport, Czech Technical University in Prague, 128 03 Prague, Czech Republic)

Abstract

The development of transport infrastructure is crucial for economic growth, social connectivity, and sustainable development. Many countries have historically underinvested in transport infrastructure, necessitating more efficient strategic planning in the implementation of transport infrastructure investment projects. This article addresses the selection and scheduling of transport infrastructure projects, specifically within the context of utilizing pre-allocated funds within a multi-annual budget investment program. The current decision-making process relies heavily on expert judgment and lacks quantitative decision support methods. We propose a genetic algorithm as a decision-support tool, framing the problem as an NP-hard 0–1 multiple knapsack problem. The proposed genetic algorithm (GA) is unique for its matrix-encoded chromosomes, specially designed genetic operators, and a customized repair operator to address the large number of invalid chromosomes generated during the GA computation. In computational experiments, the proposed GA is compared to an exact solution and proves to be efficient in terms of quality of obtained solutions and computational time, with an average computational time of 108 s and the quality of obtained solutions typically ranging between 85% and 95% of the optimal solution. These results highlight the potential of the proposed GA to enhance strategic decision-making in transport infrastructure development.

Suggested Citation

  • Karel Ječmen & Denisa Mocková & Dušan Teichmann, 2024. "Solving Transport Infrastructure Investment Project Selection and Scheduling Using Genetic Algorithms," Mathematics, MDPI, vol. 12(19), pages 1-28, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3056-:d:1488737
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    References listed on IDEAS

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