Over the last years, the food delivery market has seen significant growth and provide a lot of jobs for deliverymen. The revenue of a takeaway deliveryman depends on not only reasonable order taking but also efficient delivery path planning. However, it is challenging to select among a large number of candidate orders and plan an efficient route passing all involved pickup points and service points. In this paper, we present a problem integrating order selection and delivery path optimization for takeaway deliverymen. The objective is to maximize the revenue per unit time subject to overtime penalty and high-workload reward. To efficiently solve this problem, we propose a hybrid intelligent algorithm, which adapts the water wave optimization (WWO) metaheuristic to evolve solutions to the main order selection problem and employs tabu search to optimize the path for each order selection solution. Experimental results on test instances demonstrate the performance advantages of the proposed algorithm compared to a set of popular metaheuristic optimization algorithms.