Investigations into effectively moving people and goods

Arsik, Idil

Title:

Investigations into effectively moving people and goods

dc.contributor.advisor	Savelsbergh, Martin W. P.
dc.contributor.author	Arsik, Idil
dc.contributor.committeeMember	Erera, Alan L.
dc.contributor.committeeMember	Boland, Natashia
dc.contributor.committeeMember	Toriello, Alejandro
dc.contributor.committeeMember	Resende, Mauricio G. C.
dc.contributor.department	Industrial and Systems Engineering
dc.date.accessioned	2020-09-08T12:45:50Z
dc.date.available	2020-09-08T12:45:50Z
dc.date.created	2020-08
dc.date.issued	2020-05-19
dc.date.submitted	August 2020
dc.date.updated	2020-09-08T12:45:50Z
dc.description.abstract	In this thesis,we investigate practical methods to move people and goods effectively on the road network. In the ﬁrst part of this thesis, we focus on route guidance for the movement of people while in the second part we focus on the movement of goods by investigating the two main aspects of service network design: ﬂow and resource planning. In Chapter 2, we introduce a centralized proactive route guidance approach motivated by the anticipated introduction of autonomous vehicles which, with full adoption, can create an environment in which a speciﬁc origin-destination path can be assigned to each self-driving vehicle and in which that vehicle will follow the assigned path. Our approach integrates a system perspective, i.e., minimizing congestion, and a user perspective, i.e., minimizing inconvenience. As a design choice, we only solve linear program which is more likely to scale well and be of practical use. The linear structure of our models allows us to derive theoretical properties. In particular, we show that for the problem of minimizing maximum arc utilization, which is used as a measure of congestion in a road network, results analogous to those well-known for the maximum ﬂow problem, e.g., the max ﬂow-min cut theorem, can be derived. In Chapter 3, we focus on cost-effective routing of commodities on a line-haul network from its origin to its destination while meeting tight service requirements, satisfying operational constraints and minimizing transportation costs. We introduce a marginal cost path-based greedy heuristic that works with a partially time-expanded network to solve large scale real-life instances found in practice. Our approach involves two consolidation improvement heuristics and novel use of iterative reﬁnement within the greedy heuristic to obtain a continuous-time feasible service network design. In Chapter 4, we analyze the value of outsourcing transportation for different negotiated prices with contractors and,while doing so, explicitly account for driver considerations. We introduce a depth-ﬁrst search algorithm to generate a set of time-feasible cycles of chosen length in terms of the number of dispatches that covers a set of planned dispatches in a given load plan, where dispatches can be connected by empty travel. When generating cycles, we respect the company speciﬁc rules and hours-of-service regulations that ensure road safety and prevent fatigue related accidents. We solve an integer programming model that identiﬁes a subset of company cycles (and contractor cycles and one-way moves if the outsourcing option is available) that maximizes the cost savings over the (unrealistic) scenario in which company drivers perform a one-way move and return empty. When a company only performs out-and-back cycles, we efﬁciently choose the set of cycles by solving bipartite matching problem for each out-and-back lane pair separately.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/63610
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Route guidance
dc.subject	Service network design
dc.title	Investigations into effectively moving people and goods
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Savelsbergh, Martin W. P.
local.contributor.corporatename	H. Milton Stewart School of Industrial and Systems Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	a2cfc4e1-8f99-4246-b2c1-000ee5a8c96e
relation.isOrgUnitOfPublication	29ad75f0-242d-49a7-9b3d-0ac88893323c
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral