In a competitive market, airlines continually seek solutions that can reduce their operational costs. Flight path optimisation is a commonly pursued approach to this but requires a large amount of data about the flight environment including the weather information, the aircraft performance and the air traffic control (ATC) requirements. Existing programmes require the user to provide this aircraft performance data in advance and are incapable of generating the information on their own. In this study, using a multidisciplinary approach and numerical optimisations, a novel standalone flight path optimiser (SAFPO) solution is proposed and developed to choose the best flight path for a flight between two points in accordance with the cost objectives. SAFPO uses its own performance calculator, predefined ATC routes, and known weather information to find the optimum flight path which minimises fuel consumption and/or flight time. The aerodynamic characteristics of the aircraft are determined using a validated semi-empirical programme called MAPLA, previously developed for light aircraft analysis. Furthermore, the optimisation process consists of a multidisciplinary-feasible (MDF) framework that employs a genetic algorithm (GA) optimiser. The resulting performance characteristics of the aircraft and the optimisation process are compared with the actual information provided within the flight manual of a Beechcraft Baron G58 aircraft. The optimisation results show that SAFPO can be used to make advances in the daily operations of small and local airlines suffering from a lack of aircraft performance data and help them to choose the scenario that best accomplishes their cost objectives.