knapsack fitness function will cause GA to evaluate to NaN when max_weight_pct < 1.0

[iKuba]

def evaluate(self, state: np.ndarray) -> float:
        """Evaluate the fitness of a state vector.

        Parameters
        ----------
        state : np.ndarray
            State array for evaluation. Must be the same length as the weights
            and values arrays.

        Returns
        -------
        float
            Value of fitness function.

        Raises
        ------
        ValueError
            If `state` is not the same size as the weights and values arrays.
        TypeError
            If `state` is not an instance of `np.ndarray`.
        """
        if not isinstance(state, np.ndarray):
            raise TypeError(f"Expected state_vector to be np.ndarray, got {type(state).__name__} instead.")
        if len(state) != len(self.weights):
            raise ValueError("The state_vector must be the same size as the weights and values arrays.")

        total_weight = np.sum(state * self.weights)
        total_value = np.sum(state * self.values)

        if total_weight <= self._w:
            return float(total_value)

        return 0.0

The final line return 0.0 should probably something like return 1e-6 to avoid a 0.0.