Multi-objective Optimization of Freight Route Choices in Multimodal Transportation

Abstract

Route selection strategy has become the main aspect in the multimodal transportation system. The transport cost and time as well as the inherent risks must be considered when determining a corrective design plan. The selection of a multimodal transportation network route is a complex multi-objective decision problem. Therefore, considering the impact factors such as the transport cost, time, and comprehensive risk assessment model were further created. This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP) to determine an optimal multimodal transportation route. AHP is employed to determine weights of each factor, which rely on expert judgments. The significant weights of criteria obtained from AHP can be integrated in the objective function of ZOGP which is used to generate the optimal route. The empirical case study of coal manufacturing is conducted to demonstrate the proposed model. This methodology can provide a guidance for effectively determining the multimodal transportation routes to improve performance of logistics systems.

Multi-Objective Optimization of Customer-Centered Intermodal Freight Routing Problem Based on the Combination of DRSA and NSGA-III

“…Chang [12] and Lei et al [32] used the weighting method to integrate multiple objectives, classified the DMs' preferences using weight, and then applied the Lagrangian relaxation technique and the swarm intelligence method to solve the optimization models, respectively. Kaewfak, Ammarapala, and Huynh [33] combined 0-1 goal programming with the analytic hierarchy process to determine weights by a pairwise comparison of the objectives to generate optimal routes. There are also less studied applied posteriori methods in IFRP.…”

Multi-Compartment Vehicle Loading and Route Optimization: Case for Exporting Thai Fresh Fruits

“…Furthermore, the beverage transportation model from Thailand to Cambodia that aims to minimize cost, time, and risk has been studied [10]. The time-cost model was applied to determine the duration and expense of each route.…”

“…Constraint (9) enforces that just one edge links to a destination node. Constraints (10) and (11) ensure that the total transportation time must not exceed the allowable maximum total time; meanwhile, the maximum total time requirement must not exceed the least fresh fruit shelf life. Constraint ( 12) -(15) define the model's decision variables.…”

Evaluation of the route selection in international freight transportation by using the CODAS technique based on interval-valued Atanassov intuitionistic sets

“…Some of these techniques are the genetic algorithm (Jassbi and Makvandi 2010 ), mixed-integer linear programming (MILP) approach (Tiwari et al 2013 ), artificial neural network (ANN) theory (Qu and Chen, 2008), and the Grey Relational Analysis method (Yu et al 2005 ). Some papers also examined the route selection problems without using a mathematical model (Huynh and Fotuhi 2013 ; Bookbinder and Fox 1998 ; Marín-Tordera et al 2006 ; Kaewfak and Ammarapala 2018 ; Boardman et al 1997 ; Pham et al 2018 ; Sicilia et al 2014 ).…”