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Evaluating and Improving the Transport Efficiency of Logistics Operations
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The thesis focuses on evaluating and improving the transport efficiency of two types of logistics operations in the supply chain.

One research area is the production of raw material in construction operations, specifically earthmoving operations. Methods and tools are developed to provide decision support in improving the transport efficiency of earthmoving at the vehicle and the systems levels. Using known road topography and a GPS unit, an optimal control problem is formulated and solved (Paper III) to determine the optimal gear shift sequence and timing in order to improve the transport efficiency at the vehicle level. For decision support at the systems level, a Fleet Performance Simulation (FPS) model is designed (Paper IV) to evaluate the transport efficiency for a given mix of construction vehicles in earthmoving. The FPS system is integrated with an optimization algorithm to solve the optimal fleet composition problem for earthmoving operations (Paper V & VI). Construction operations are dynamic and the environment is changing constantly, which bring difficulties in decision-making. Using GPS data from construction vehicles, a map inference framework (Papers I & II) is developed to automatically extract relevant input to decision support at the vehicle and the systems levels, which include the locations of various workstations, driving time distributions and road networks.

The second research area is the transport efficiency of urban distribution system, which is in the final phase of the supply chain. An off-peak delivery pilot project in Stockholm is used as the background, designed to evaluate the potential for commercial vehicles to make use of off-peak hours for goods delivery. The thesis (Paper VII) evaluates the transport efficiency impacts of the off-peak pilot. An evaluation framework is defined where transport efficiency is studied in a number of dimensions. GPS data, fleet management data, and logistic information are used to assess the impacts.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2017. , p. 47
Series
TRITA-TSC-PHD ; 17-002
Keywords [en]
transport efficiency, earthmoving operations, off-peak urban deliveries, simulation, optimization, GPS data
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
URN: urn:nbn:se:kth:diva-204030ISBN: 978-91-87353-99-4 (electronic)OAI: oai:DiVA.org:kth-204030DiVA, id: diva2:1083891
Public defence
2017-04-28, Kollegiesalen, Brinellvägen 8, Stockholm, 14:00 (English)
Opponent
Supervisors
Funder
Integrated Transport Research Lab (ITRL)
Note

QC 20170323

Available from: 2017-03-23 Created: 2017-03-22 Last updated: 2024-01-04Bibliographically approved
List of papers
1. Identification of workstations in earthwork operations from vehicle GPS data
Open this publication in new window or tab >>Identification of workstations in earthwork operations from vehicle GPS data
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Increasing availability and the use of Global Positioning System (GPS) devices open great opportunities for various transportation applications. The authors propose a generative probabilistic model for extraction of locations of workstations in earthwork operations using raw GPS traces from construction vehicles. The probabilistic model incorporates the GPS measurements with relevant information extracted from the GPS data to compute locations of different workstations as probability distribution over the environment. The location of workstations will be used as a part of a map inference method for generating and continuously updating the layout and road network topology of the construction environment. A detailed case study was conducted with construction equipment at a complex site. The authors first demonstrate the probabilistic model to extract the locations of loading stations using vehicle speed and interactions among vehicles, and then to discover dumping stations with help of vehicle moving patterns. The results from the experiment show that the proposed method is able to discover important places and workstations for earthwork environment efficiently and in sufficient details.

Place, publisher, year, edition, pages
Transportation Research Board, 2016
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-200576 (URN)
Conference
Transportation Research Board 95th Annual Meeting
Note

QC 20170201

Available from: 2017-01-30 Created: 2017-01-30 Last updated: 2022-06-27Bibliographically approved
2. Driving time and path generation for heavy construction sites from GPS traces
Open this publication in new window or tab >>Driving time and path generation for heavy construction sites from GPS traces
2016 (English)In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, IEEE, 2016, p. 1141-1146Conference paper, Published paper (Refereed)
Abstract [en]

The paper presents a methodology for using GPS probe data to automatically extract the driving time between workstations and build a detailed representation of the paths between workstations in a construction environment. The inferred driving time distribution is aimed as input to construction simulation models to assess fleet performance, while the path information can be utilized to examine the performance of individual vehicles. A case study, using GPS data collected from a construction site, is used to demonstrate the capability of the proposed approach. The GPS data are processed without any prior knowledge about the underlying work environment. The results show that the proposed approach is capable of accurately inferring the driving time distribution and the paths between workstations.

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-200584 (URN)10.1109/ITSC.2016.7795700 (DOI)000392215500179 ()2-s2.0-85010061504 (Scopus ID)9781509018895 (ISBN)
Conference
19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016; Windsor Oceanico HotelRio de Janeiro; Brazil; 1 November 2016 - 4 November 2016
Note

QC 20170130

Available from: 2017-01-30 Created: 2017-01-30 Last updated: 2022-06-27Bibliographically approved
3. Gear shift optimization for off-road construction vehicles
Open this publication in new window or tab >>Gear shift optimization for off-road construction vehicles
2014 (English)In: European Journal of Transport and Infrastructure Research, ISSN 1567-7133, Vol. 14, no 3, p. 214-228Article in journal (Refereed) Published
Abstract [en]

This paper explores the possibility of using recorded road slope data in order to reduce fuel consumption for off-road construction vehicles such as articulated haulers. Road gradients have strong influence on the fuel consumption of a vehicle. This effect is even more significant on construction vehicles due to their large mass and heavy load. In this study, a control algorithm based on model predictive control and dynamic programming is formulated and solved to find an optimal gear shift sequence and time of shifting. The fuel consumption model of an articulated hauler is formulated with a dynamic model and used together with the travel time in the objective function to balance the trade-off between these two aspects. The proposed control algorithm is simulated on a typical road stretch on the construction work site with frequent steep up- and downhill. Simulation shows that both fuel consumption and travel time can be reduced simultaneously. In addition, the optimal gear shift sequence resembles the behaviour of an experienced driver.

Keywords
Discrete dynamic programming, fuel efficiency/consumption, gear shift optimization, model predictive control, off-road construction vehicle
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-158297 (URN)10.18757/ejtir.2014.14.3.3031 (DOI)000345856000003 ()2-s2.0-84906955941 (Scopus ID)
Note

QC 20150109

Available from: 2015-01-09 Created: 2015-01-07 Last updated: 2024-03-18Bibliographically approved
4. A Microscopic Simulation Model for Earthmoving Operations
Open this publication in new window or tab >>A Microscopic Simulation Model for Earthmoving Operations
2012 (English)In: Proceedings of the International Conference on Sustainable Design and Construction, 2012, p. 218-223Conference paper, Published paper (Refereed)
Abstract [en]

Earthmoving operations are a major part of many construction projects. Because of the complexity and fast-changing environment of such operations, the planning and estimating are crucial on both planning and operational levels. This paper presents the framework ofa microscopic discrete-event simulation system for modeling earthmoving operations and conducting productivity estimations on an operational level.A prototype has been developed to demonstrate the applicability of the proposed framework, and this simulation system is presented via a case study based on an actual earthmoving project. The case study shows that the proposed simulation model is capable of evaluating alternative operating strategies and resource utilization at a very detailed level.

National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-115982 (URN)
Conference
the International Conference on Sustainable Design and Construction
Note

TSC import 2106 2013-01-15. QC 20130531

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2024-03-18Bibliographically approved
5. Simulation-Based Optimization of Earthmoving Operations Using Genetic Algorithm
Open this publication in new window or tab >>Simulation-Based Optimization of Earthmoving Operations Using Genetic Algorithm
2012 (English)In: Proceedings of the 17th International Conference of Hong Kong Society for Transportation Studies, 2012, p. 57-64Conference paper, Published paper (Refereed)
Abstract [en]

Earthmoving operations are a fundamental part of heavy construction projects. From the project manager's point of view, understanding of both productivity and cost estimations is indispensable. Equipment selection is an important factor in the resulting productivity and cost of operations. Traditionally, the equipment selection is performed based on experience and rules of thumb. This paper presents a framework of simulation-based optimization of resource selection in earthmoving operations by integrating a discrete-event simulation platform with a genetic algorithm. The simulation engine evaluates the performance (fitness) of each equipment combination and the genetic algorithm searches for an optimal equipment configuration while considering a set of qualitative and quantitative decision variables which influence the performance of earthmoving operations. A prototype has been developed to demonstrate the applicability of the proposed framework. Pilot simulation runs show that this system can effectively locate a near optimal equipment combination for earthmoving operations. The proposed simulation optimization framework can hence serve as an efficient tool for project management in fleet selection.

National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-115980 (URN)000367757500007 ()2-s2.0-84896854386 (Scopus ID)
Conference
The 17th HKSTS International Conference
Note

TSC import 2104 2013-01-15. QC 20130531

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2022-06-24Bibliographically approved
6. Optimal Fleet Selection for Earthmoving Operations
Open this publication in new window or tab >>Optimal Fleet Selection for Earthmoving Operations
2013 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Earthmoving operations often involve a large number of specially designed equipment with significant purchasing/leasing prices, high operating and maintenance costs. Hence, choosing the right fleet is a major concern from the construction planners’ point of view. This paper presents a methodology that combines discrete-event simulation and optimization to solve the optimal fleet selection problem for earthmoving operations. Two optimization objectives are formulated and solved using the proposed framework and a genetic algorithm: minimization of Total Cost of Ownership (TCO) and maximization of productivity. Further, a two-stage rating scheme is introduced to arrange the fleet configurations so that the optimization algorithm converges to a fleet with better second-stage performance while the first-stage performance remains at the same level. The case study shows that the proposed mechanism can effectively allocate an optimal equipment combination for earthmoving operations and hence serve as an efficient tool for construction management.

Keywords
earthmoving operations, equipment selection, simulation optimization, discrete - event simulation, genetic algorithm .
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-115983 (URN)
Conference
ISEC 7.7th International Structural Engineering and Construction Conference,Honolulu, Hawaii
Note

TSC import 2107 2013-01-15. QC 20130531

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2024-03-18Bibliographically approved
7. Transport efficiency of off-peak urban goods deliveries: A Stockholm pilot study
Open this publication in new window or tab >>Transport efficiency of off-peak urban goods deliveries: A Stockholm pilot study
2017 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Transportation Research Board, 2017
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-200587 (URN)
Conference
the 96th Annual Meeting of the Transportation Research Board (TRB)
Note

QC 20170130

Available from: 2017-01-30 Created: 2017-01-30 Last updated: 2022-06-27Bibliographically approved

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Output format
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