Urban congestion is an increasing challenge for accessibility, travel times and livability. Although on-demand water cabs offer a flexible and sustainable alternative, the design of optimal mooring locations has been underexplored. To address this problem, this article presents a new method for the strategic placement of mooring locations. The proposed method involves identifying potential mooring locations and applying a customised Adaptive Large Neighbourhood Search (ALNS) to manage computational complexity. The model minimises weighted travel time and cost indicators for all origin destination pairs by selecting between public transport and water cab for each trip. The method was evaluated in a case study of Rotterdam. The findings indicate that the proposed ALNS algorithm outperforms both Large Neighbourhood Search (LNS) and Mixed-Integer Linear Programming (MILP) in computation time while simultaneously generating high quality solutions. Moreover, the model is shown to be capable of identifying an efficient network, resulting in greater coverage, shorter travel times and improved accessibility. These results demonstrate that the method constitutes a powerful tool for policymakers in designing robust, efficient and future proof water cab networks.