An optimization framework for management of transportation infrastructure systems with interdependent facilities.

摘要

The extensive amount of maintenance expenditures on transportation infrastructure systems and their broad impacts in terms of economic and social development has emerged the interests in maintenance management of transportation infrastructure systems. This dissertation contributes an optimization framework for management of transportation systems that comprise of interdependent facilities.; Existing stochastic, single-facility, maintenance optimization models allow the interpretation of the results to support management decisions of the multiple facilities systems. However, the aforementioned models sacrifice important functional characteristics in favor of computational tractability/simplicity. However, omitting information that identifies the individual facilities makes it impossible to capture interdependencies that link them. An approach often uses to address the limitations is to consider the multiple facilities models to support management decisions of the multiple facilities systems. The multiple facilities models are flexible but always suffer from computational limitations that make them impractical to support decision making of multiple facilities systems. We present a quadratic programming formulation for the problem of obtaining optimal maintenance and repair policies for multi-facility transportation infrastructure systems. The proposed model provides a computationally-tractable framework to support decision-making, while accounting for economic and functional interdependencies that link the facilities that comprise these systems.; To demonstrate the advantages of the proposed model, we present two applications. In the first application, the formulation captures economic interdependencies reflecting both costs associated with disruptions/loss of throughput, as well as the benefits associated with coordinating intervention schedules of adjacent facilities to reduce costs associated with resource and personnel delivery. In the second application, the formulation explicitly captures the bidirectional relationship between demand and deterioration. That is, the state of a facility, i.e., its condition or capacity, impacts the demand/traffic. Simultaneously, demand determines a facility's deterioration rate. The elements that comprise transportation systems are linked because the state of a facility can impact demand at other facilities. In each application, we provide a series of numerical examples to illustrate the advantages of the proposed framework. The results illustrate situations where it is optimal to coordinate (synchronize or alternate) interventions for clusters of facilities in transportation systems.