This study describes a Mixed-Integer Linear Programming (MILP) model for optimizing the costs of CO₂ transport network infrastructure, involving multiple modes of transport (pipelines, trucks, trains, and ships) and the required conditioning and processing steps, for industrial Carbon Capture, Utilization and Storage (CCUS) projects. The model assumes varied amounts of CO2 transported from the emission sources and accounts for essential factors, such as geographical locations of CO2 emitters, injection points of geological storage, interim storage locations at seaports, and CO2 transportation routes. To be more accurate and realistic, the model involves conditioning functions based on the pressure requirements of upstream and downstream transport systems, offering a precise representation of conditioning change processes. A case study is constructed to compare the costs and optimal transport network designs for various amounts of CO2 transported from a set of industries in Western Europe. The results highlight the economic viability of flexible, multi-modal systems for small-scale applications, transitioning to pipelines for larger volumes. This work offers critical insights into scalable CO2 transport solutions, supporting efficient CCUS deployment in the near future.