Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function

An efficient online delivery system in the dynamic landscape is a challenging task. The challenges occur due to the difficulty in generating a proper objective function that can represent the performance of the delivery system. In this paper, we propose a novel multi-objective function that represents the utility score and time required in the delivery process. The utility score takes into consideration the number of previous orders given by a particular customer and the Time window methodology is used to achieve the two objectives. The multi-objective optimization functions are solved and compared using three multi-objective algorithms. They are Non-dominated sorting genetic algorithm-II (NSGA-II), strength Pareto evolutionary algorithm 2 (SPEA2), and indicator-based evolutionary algorithm (IBEA). The performances are compared extensively and it is found that SPEA2 gives better convergence performance. The proposed objective function minimizes the limitation of currently available methods for online delivery systems.