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Regulating the rebound effect in the traveling purchaser problem.

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Title: Regulating the rebound effect in the traveling purchaser problem.
Authors: Caballero, William N.1 (AUTHOR) william.caballero@us.af.mil, Lunday, Brian J.2 (AUTHOR), Meissner, Finn3 (AUTHOR)
Source: European Journal of Operational Research. Sep2024, Vol. 317 Issue 3, p660-677. 18p.
Subjects: Bilevel programming, Technological innovations, Climate change, Energy consumption, Package tours
Abstract: • A bilevel traveling purchaser program is developed to mitigate the rebound effect. • The regulator seeks to reduce resource consumption by minimally disrupting commerce. • Mathematical properties are proven regarding each agent's best response. • Custom solution methodologies are developed based upon the derived properties. • Designed experiments are used to statistically characterize each solution method. Despite engineers' best intentions, technological innovations intended to reduce resource consumption are not assured to achieve their desired effects. As self-interested agents utilize the technological innovation, theretofore unprofitable activities may be rendered profitable, leading to a disparity between the expected reduction in resource consumption and what is actually achieved. This rebound effect is particularly salient given the current global climate crisis. In practice, many national governments are promoting fuel efficiency gains via new, cutting-edge technologies. However, to maximize the effectiveness of such technological innovations, additional regulation is likely required to avoid unfavorable rebound effects. To further study the dynamics of this setting, we set forth a logistics-based Stackelberg game underpinned by the Traveling Purchaser Problem. More specifically, we develop a bilevel programming formulation wherein the upper-level player is a regulator and the lower-level player is the purchaser. The regulator encounters a multi-objective problem and desires to reduce resource consumption while minimally disrupting commerce on the network. Mathematical conditions are derived and proved to determine when the null regulator action is optimal. These results are leveraged to develop a preprocessing algorithm and customized heuristic solution methodology. Extensive empirical testing is conducted on these methods and their results are analyzed using statistical techniques to quantitatively characterize their behavior. Analysis confirms the supposition that regulation and technological innovations are often required in tandem to achieve a regulator's aims; however, it also reveals that, under select conditions, the regulator is better served by not intervening. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Operational Research is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 177564363
AccessLevel: 6
PubType: Academic Journal
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  Data: Regulating the rebound effect in the traveling purchaser problem.
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Operational+Research%22">European Journal of Operational Research</searchLink>. Sep2024, Vol. 317 Issue 3, p660-677. 18p.
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– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • A bilevel traveling purchaser program is developed to mitigate the rebound effect. • The regulator seeks to reduce resource consumption by minimally disrupting commerce. • Mathematical properties are proven regarding each agent's best response. • Custom solution methodologies are developed based upon the derived properties. • Designed experiments are used to statistically characterize each solution method. Despite engineers' best intentions, technological innovations intended to reduce resource consumption are not assured to achieve their desired effects. As self-interested agents utilize the technological innovation, theretofore unprofitable activities may be rendered profitable, leading to a disparity between the expected reduction in resource consumption and what is actually achieved. This rebound effect is particularly salient given the current global climate crisis. In practice, many national governments are promoting fuel efficiency gains via new, cutting-edge technologies. However, to maximize the effectiveness of such technological innovations, additional regulation is likely required to avoid unfavorable rebound effects. To further study the dynamics of this setting, we set forth a logistics-based Stackelberg game underpinned by the Traveling Purchaser Problem. More specifically, we develop a bilevel programming formulation wherein the upper-level player is a regulator and the lower-level player is the purchaser. The regulator encounters a multi-objective problem and desires to reduce resource consumption while minimally disrupting commerce on the network. Mathematical conditions are derived and proved to determine when the null regulator action is optimal. These results are leveraged to develop a preprocessing algorithm and customized heuristic solution methodology. Extensive empirical testing is conducted on these methods and their results are analyzed using statistical techniques to quantitatively characterize their behavior. Analysis confirms the supposition that regulation and technological innovations are often required in tandem to achieve a regulator's aims; however, it also reveals that, under select conditions, the regulator is better served by not intervening. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of European Journal of Operational Research is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.ejor.2022.06.045
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        Text: English
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        PageCount: 18
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        Type: general
      – SubjectFull: Technological innovations
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      – SubjectFull: Climate change
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      – SubjectFull: Energy consumption
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      – SubjectFull: Package tours
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              M: 09
              Text: Sep2024
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              Y: 2024
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