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This change adds configurable fitness-function support to the Genetic Algorithm, allowing optimization for shortest distance in addition to the default fuel-based objective. The RoutingProblem now accepts a fitness_function_type parameter and returns both fuel and distance metrics. GA execution logic selects the fitness strategy based on ALGORITHM_TYPE, enabling shortest-route optimization via genetic_shortest_route. A new test file was added to validate this configuration, though full execution is blocked by missing local dependencies.

This change adds configurable fitness-function support to the Genetic Algorithm, allowing optimization for shortest distance in addition to the default fuel-based objective. The RoutingProblem now accepts a fitness_function_type parameter and returns both fuel and distance metrics. GA execution logic selects the fitness strategy based on ALGORITHM_TYPE, enabling shortest-route optimization via genetic_shortest_route. A new test file was added to validate this configuration, though full execution is blocked by missing local dependencies.
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