It is paramount to perform timely and appropriate maintenance actions on networked infrastructures, such as power transmission, transportation, telecommunications, and so forth, in order to ensure their reliability in satisfying the prescribed demand required by the economic development and social well-being of a society. For this purpose, the time of travelling between the components to be maintained needs to be considered, as the components of a real-world infrastructure are usually geographically widely distributed. To address this problem, we propose a holistic bi-objective optimization approach for the joint optimization of maintenance planning and workforce routing for a networked infrastructure, in order to determine a practical maintenance plan that can simultaneously maximize its reliability and minimize the incurred cost. To deal with the complexity of the proposed problem, we develop a Two-level Pareto Simulated Annealing algorithm to approximate the Pareto-optimal solutions of the proposed problem. Finally, two numerical examples are employed to illustrate the ability of the proposed approach in dealing with the maintenance optimization problem of a geographically distributed networked infrastructure.

This paper studies the joint optimization of price and two-dimensional (2-D) warranty policy with limits of both warranty length and usage. For this purpose, in this paper, we first propose a new sales function to characterize the joint influence of price, warranty length, and usage limit on the sales rate while considering the influence of the heterogeneous customer usage rate. Then, we model the joint dynamic optimization of price and 2-D warranty policy as a nonlinear optimal control problem, and solve it via a numerical approach based on Pontryagin's maximum principle. We show that the proposed dynamic 2-D warranty policy can help achieve higher profits than the existing one-dimensional policies and static 2-D policy.