The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is a multicriteria technique that ranks alternatives based on their closeness to an ideal solution (maximum performance on all criteria) and an anti‑ideal solution (minimum performance). In urban transport, analysts define a set of weighted criteria: e.g., CO₂ emissions (high weight), capital costs (medium weight), passenger capacity (high weight), noise impact (medium weight) and integration with existing network (high weight).
Alternatives (metro, tram, monorail, BRT) are evaluated on a normalized scale, converting absolute values into comparable scores. Euclidean distances from each alternative to the ideal and anti‑ideal solutions are then calculated. The closeness index (C*) is the ratio of the distance to the anti‑ideal over the sum of both distances; the closer C* is to 1, the more preferable the alternative.
An additional step applies binding criteria, such as a minimum passenger capacity or a maximum emission threshold. Alternatives failing these constraints are removed before the TOPSIS calculation, reducing computational load and focusing the analysis on realistic options.
The final output is a ranking that highlights trade‑offs: metros excel in capacity and speed but require high investment; trams offer a good balance of cost and urban integration; monorails can reduce spatial footprint but have limited capacity; BRT is cheap and flexible but may cause congestion if not properly managed.
Practical application demands local data collection (traffic flows, land costs, policy incentives) and stakeholder input to set appropriate weights and thresholds. Sensitivity analysis can test how changes in weights affect the ranking, ensuring robust decisions.
In summary, TOPSIS provides a transparent, repeatable framework for comparing public‑transport projects, helping decision‑makers select the option most aligned with urban sustainability goals.
