Work

A hybrid optimization and microsimulation framework for simulating weekly travel activities

Year: 2026

Type: article

Abstract: This paper introduces a simulation-based optimization framework to simulate weekly travel activities from single-day data, addressing the diminishing relevance of a "Typical Day." The framework builds on the integrated land use and energy modeling system (iTLE), combining long- and short-term decision components, a Markov Chain Monte Carlo (MCMC)-based activity generator, and an activity scheduler. The optimization model accounts for individual travel preferences through constraints, iteratively calibrating activity transition probabilities to match desired weekly travel patterns. Key activities simulated include in-home work (IHW), in-person work, shopping, eating out, and recreation. Calibration results show deviations of 19.0%, 16.4%, and 15.2% for IHW, in-person work, and shopping, respectively, with validation deviations of 4.3% for eating out and 2.3% for recreation. The model highlights distinct work patterns and commute behaviors, offering flexibility for post-pandemic transportation planning policies.

Source: Computational Urban Science

DOI: 10.1007/s43762-026-00259-4

Authors: MD Jahedul Alam, Md. Rifat Hossain Bhuiyan, Venkata Vijaya Rama Raju Mandapati, Muhammad Ahsanul Habib

Institution: Dalhousie University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: diamond

Funder: Natural Sciences and Engineering Research Council of Canada