Abstract This paper contributes to the existing research on freight transportation, spatial and land use planning by investigating an improved spatial aggregation technique to delineate desirable freight traffic analysis zones. Zoning is a process of spatially aggregating several predefined basic spatial units (BSUs) into multiple zones. It plays a vital role in the transportation planning and decision-making process and is well-documented as the modifiable areal unit problem (MAUP). MAUP involves aggregating BSUs to obtain optimal zones satisfying specific criteria and constraints. This paper proposes an improved spatial aggregation methodology to develop a freight traffic analysis zone system by applying the multiobjective optimization concept using a genetic algorithm. The decision variables, namely, (i) Freight trip density; (ii) Number of establishments; (iii) Employment density; and (iv) Compactness, are chosen to represent the elements of freight, passenger traffic, and land use. The problem is formulated as a multiobjective network partitioning problem. The four objectives aim to create zones with better homogeneity and compactness. It is solved using a genetic algorithm with a weighted distance metric approach to prioritize the four objectives. Results show that zones resulting from the improved methodology are superior to the existing zones in terms of homogeneity of decision variables and compactness. The findings are expected to help the decision-making process of urban, transportation, and land-use planners in selecting appropriate freight traffic zone delineation strategies for a given region.

    Highlights Multiobjective optimization concept is applied to develop freight traffic analysis zones (FTAZ) Decision variables represent the characteristics of freight, passenger traffic, and land use. Weighted distance metric approach using a genetic algorithm is used to prioritize zoning objectives Findings suggest that FTAZs are superior to existing zones in homogeneity and compactness


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning


    Contributors:


    Publication date :

    2021-03-26




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Intelligent Zoning Design Using Multi-Objective Evolutionary Algorithm

    Radtke, P. / Oliveira, L. / Sabourin, R. et al. | British Library Conference Proceedings | 2003



    Freight Transportation Planning

    Schank, Joshua / Hirschman, Ira / Elliott, Preston | Transportation Research Record | 2008



    Intelligent zoning design using multi-objective evolutionary algorithms

    Radtke, P.V.W. / Oliveira, L.S. / Sabourin, R. et al. | IEEE | 2003