Mode choice in strategic freight transportation models: a constrained Box–Cox meta-heuristic for multivariate utility functions
(2021) Transportmetrica A: Transport Science — p. 1-21 (2021)
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- Abstract
- Modal choice models used for freight transportation studies covering inter-regional or international areas are difficult to set up because of the dearth of information about explanatory factors. While cost and transit time are known as being important explanatory variables, they are generally correlated to each other, and their coefficient computed with a Logit model can have unexpected signs. Box-Cox transformations (BCT) of the independent variables can help to overcome this problem. If solutions to identify the BCT parameter that maximises the likelihood of a model are well known, the process is not straightforward once it must respect the constraints that the variables’ coefficient estimators take the expected signs. This paper presents a shotgun hill climbing meta-heuristic with backtracking capabilities, able to quickly identify Box-Cox parameters to use when multiple variables must be transformed. The algorithm appears to be efficient and effective and produces stable and statistically valid solutions.
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Citations
Jourquin, B. (2021). Mode choice in strategic freight transportation models: a constrained Box–Cox meta-heuristic for multivariate utility functions. Transportmetrica A: Transport Science, 1-21. https://doi.org/10.1080/23249935.2021.1937375 (Original work published 2021)