Port Hinterland Estimation and Optimization for Intermodal Freight Transportation Networks

Abstract

Ports are considered as critical transfer terminals in switching containers between maritime and inland transportation modes. Port hinterland is a key performance indicator reflecting the competitiveness of a port. From the point of view of port operators, there is a need to estimate and optimize port hinterland, so as to facilitate their knowledge of current port market areas and to make well-informed changes to maximize their port market shares. Though practically necessitated, unfortunately, these two issues have not been fully addressed in the past relevant studies. This work is focused primarily on developing a modeling approach for port hinterland estimation and optimization. To achieve this goal, a new definition of probabilistic port hinterland is proposed. Two mathematical models are developed to formulate the attribute- and utility-based probabilistic hinterland of a particular port based on the behavior assumption of intermodal operators in route choice, respectively. Monte Carlo based algorithms are designed to solve these two models, respectively. Illustrative examples are given to assess the applicability of the proposed models and algorithms. After having the port hinterland estimated, a port hinterland optimization problem is subsequently concerned. To serve to tackle the port hinterland optimization problem, this work also aims to solve a novel intermodal hub-and-spoke network design (IHSND) problem. The IHSND problem is complicated by involving mode changes, multiple stakeholders and multi-type containers. A mathematical program with equilibrium constraints (MPEC) model is first developed to formulate the IHSND problem with uni-type containers. The model utilizes a transportation cost function having a U-shaped unit cost function to describe the cost structure of carriers and a utility function integrating actual transportation rates and congestion impact to describe the preference of intermodal operators. Two fixed-points formulations are incorporated into the MPEC model to reflect the stochastic user equilibrium based behavior assumption of intermodal operators in route choice. A branch-and-bound algorithm embedded with a cost averaging (CA) algorithm is proposed to solve the model. Another MPEC model is developed to formulate the IHSND problem with multi-type containers. In the model, a joint cost function of multi-type containers that can describe the multi-type container transportation cost structure is utilized for carriers. A utility function integrating actual transportation charges and congestion impact is proposed for intermodal operators. The model incorporates a variational inequality (VI) to represent the user equilibrium based route choice behavior of intermodal operators. Due to the non-convexity and complexity of the model, a hybrid genetic algorithm (HGA) is designed to solve the model. The proposed model and algorithm are assessed by numerical examples. Based on the investigation of the port hinterland estimation and IHSND problems, a port market share optimization (PMSO) problem with respect a concerned study area is proposed to address the port hinterland optimization problem. The PMSO problem is formulated as an MPEC model and then solved by using a branch-and-bound algorithm. The optimal market share of the port of Shenzhen and the corresponding market shares of selected Asian ports are computed by using the proposed model and algorithm. This work is believed to contribute new theories and methodologies to current literature of port competitiveness and intermodal network design studies.