Public transport operators relying on diesel fleets face increasing pressure to adopt environmentally sustainable solutions. Integrating electric vehicles into existing systems represents a promising but complex transition, requiring system-level planning under multiple, policy-oriented scenarios. This study adopts a systems science perspective to address this challenge, recognising the interdependencies among fleet composition, battery technologies, charging infrastructure and policy constraints. To support integrated decision-making, it introduces a mixed-integer linear optimisation model—the MultOptMixedFleet—that determines the optimal mix of electric and non-electric buses, selects suitable battery capacities and identifies strategic charging locations and types. The model formulates fleet electrification as a multi-objective optimisation problem, capturing trade-offs between cost and environmental performance. Applied to a Portuguese public transport provider, the model demonstrates its practical value as a decision-support tool for managers and policymakers seeking cost-effective and low-emission transition strategies. Results show that progressive electrification delivers major emission reductions: fully replacing diesel buses lowers emission-related costs by approximately 67% compared with fully non-electric fleets. Although electrification increases total system costs, longer battery lifecycles mitigate this effect by reducing annual operating and investment costs by 6% and 33%, respectively. Overall, the study highlights the importance of systems-oriented modelling for sustainable operations and logistics.

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Multiple objective programming,Decision support tool,Mixed fleet,Bus operations,Environmental concerns

• Economics and Business - Social Sciences