Optimizing the selection and scheduling of multi-class projects using a Stackelberg framework

One of the major causes of non-recurrent traffic congestion in urban areas is the implementation of transport infrastructure projects on city roads. The seeming ubiquity of work zones in cities causes road user frustration and safety hazards, and public relations problems for the transport agency. For this reason, transport agencies seek strategic ways to not only select urban projects but also schedule them in a manner that minimizes the effort associated with these functions. In other words, they seek to exploit the synergies between the tasks of project selection and project scheduling while duly accommodating the project interdependencies. This study introduces a general framework that simultaneously and optimally selects and schedules urban road projects subject to budgetary constraints over a given planning horizon. The project classes considered in this study are lane addition, new road construction, and road maintenance. Through a mimicry of the classic Stackelberg leader-follower game, this problem is formulated herein as a bi-level program. In the upper level, the leader (transport agency decision-makers) determines an optimal set of projects from a larger pool of candidate projects and decides an optimal schedule for their implementation. In the lower level, the followers (road users) seek to minimize their travel delays based on the two decisions made by the leader in the upper level. The numerical experiments show that if the decision-makers do not consider the peri-implementation capacity reduction, the resulting set of selected projects and their construction schedule can lead to significant travel delay cost for the road users. © 2020 Elsevier B.V.