Multiple objective decision-making in the mode choice problem: a goal-programming approach

Mode choice is one of the important stages in the transportation planning model, by which decision-makers can estimate the number of commuters using each specified mode of transport in each given origin–destination pair. Multinomial logit models derived from the discrete choice analysis and mathematical programming models from the concept of maximum entropy are most widely used in the application to the mode choice problem. This paper aims to extend the developed entropy-based model to provide an alternative approach to that of the mode choice problem with multicriteria decision-making other than the conventional linear stochastic model. A goal-programming model is proposed to solve a multi-objective mode choice problem that involves three objectives, i.e. (1) maximization of the interactivity of the system, (2) minimization of the travel costs and (3) minimization of the deviation from the observed year. A set of Hong Kong data has been used to test the effectiveness and efficiency of the proposed model. Results demonstrate that decision-makers can find the flexibility and robustness of the proposed model by adjusting the weight factors with respect to the importance of each objective.