We formulate a bi-objective distribution model for urban trips constrained by origins and destinations while maximizing entropy. We develop a flexible and consistent approach in which the estimations of generated/attracted parameters are fuzzy with entropic membership functions. Based on a fuzzy-entropy approach, we measure the uncertainty associated with fuzzy variables. We solve the problem by means of compromise programming considering a weighted sum objective function. We compute and extend concepts such as accessibility, attractiveness, and generalized cost, typically obtained in transport economic analyzes. Considering that our formulation is convex, we solve the problem in one step only, maintaining the uniqueness of the the optimization problem solution. We present two numerical examples to illustrate the proposed methodology, analyzing the impact of the results based on strong mathematical and statistical arguments. Finally, we show that our approach has better prediction capabilities than traditional fuzzy models regarding aggregated indicators and structural distribution patterns.
Bibliographical noteFunding Information:
The authors are grateful for the financial support provided under Projects ANID/FONDECYT/Regular 1191200, CONICYT/FONDECYT 11160320, Instituto Sistemas Complejos de Ingeniería (ANID PIA/APOYO AFB180003) and project 4.148 of Fundación para la Promoción de la Investigación y la Tecnología. Banco de la República. Colombia.
© 2021 Hong Kong Society for Transportation Studies Limited.
- Entropy optimization
- Fuzzy entropy
- Fuzzy sets
- Origin-destination trip matrix
- Transport distribution