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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 81
PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: B.H.V. Topping
Paper 74

GIS Support for Optimizing Infrastructure Programs of Distributed Sites

T. Hegazy

Department of Civil Engineering, University of Waterloo, Ontario, Canada

Full Bibliographic Reference for this paper
T. Hegazy, "GIS Support for Optimizing Infrastructure Programs of Distributed Sites", in B.H.V. Topping, (Editor), "Proceedings of the Tenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 74, 2005. doi:10.4203/ccp.81.74
Keywords: infrastructure, GIS, scheduling, optimization, resource management.

Summary
In recent years, interest in developing efficient asset management systems for infrastructure networks, such as highways, bridges, airports, and water/sewer systems, etc., has grown rapidly to help sustain infrastructure services. Existing asset management systems concern mainly with developing a prioritized list of capital assets for maintenance and repair (M&R) purposes that if executed properly will lead to minimum life cycle cost and maximum serviceability. With the development of the priority list, however, the majority of asset management systems leave the delivery details to the experience of internal personnel, with little or no decision support regarding the execution sequence, resource use, and time/cost optimization. This represents a major challenge that can lead to cost overruns and delays.

Currently, many software tools for maintenance management are available. Some of these systems provide traditional planning and scheduling features, such as bar charts, to schedule operations. While these systems are beneficial, they address some but not all aspects of infrastructure execution planning. They are not formulated to respect a given deadline and do not consider the distributed and repetitive nature of operations. In addition, they provide no decision support for cost optimization and do not legibly present the large amount geographically dispersed data, particularly related to the assignment of resources among the sites. These limitations are mainly due to inadequate resource management abilities, which are crucial for infrastructure networks. As such, the need has emerged for a new decision support tools that relate to infrastructure networks in terms of the number of crews/contractors to use, the construction methods to employ in each activity, and the sites' execution order.

This paper introduces a scheduling model and an implementation software program, BAL, for optimizing resource allocation in challenging infrastructure projects with multiple-distributed locations. The paper demonstrates the applicability of this tool for efficiently managing construction and/or maintenance operations in large infrastructure networks, such as buildings, highways, bridges, and water/sewer systems. Two unique aspects of the program are discussed in this paper: (1) the underlying Geographic Information System (GIS); and (2) the powerful scheduling engine that optimizes the execution plan.

The GIS component of BAL uses a commercial software, Microsoft MapPoint 2002, to store and represent various levels of information about the scattered sites involved in a construction/maintenance program. Pre-planning information includes location, local weather, land survey data, traffic volume, etc., which varies from one site to the other. Using this information, the GIS system automatically calculates the distances from one site to any other, considering the shortest travel routes. Once the distances are calculated, the GIS system then calculates the travel time from each site to any other, considering the speed limits specified for the highways or local roads along a route. These are then directly used to determine the time and cost to transport resources from one site to the other.

During the planning stage, BAL's scheduling engine stores the user-input data of available resources, construction methods, and the time/cost/other constraints. The scheduling engine then runs a Genetic Algorithm (GA) procedure that experiments with thousands of random solutions until an optimum is reached. For each random solution, the GA selects the number of crews to use, the site order, and a set of construction methods. Accordingly, the GIS system feeds the associated distances, moving time, and moving cost to be used in the schedule. At the end of the GA procedure, an optimum work schedule is determined that respects the time, cost, and resource constraints. The schedule synchronizes the work of crews and optimizes their routing among the various sites, considering local productivity conditions and movement time/cost. Based on the optimized schedule, another layer of GIS information is generated; containing activities' start and finish dates at the various sites along with the assigned crews. This layer of information is then used by a macro written on the GIS system to present the schedule and the work assignment in a legible manner to the various project participants. One of the outputs is a legible crew assignment map, along with bar charts with start and finish times.

An example application was used to illustrate the benefits of using GIS to support schedule computation and better visualization of multiple-site multiple-crew execution plans. The proposed computer program is potentially usable by municipalities and owner/contractor organizations administering a large number of infrastructure assets, such as buildings, highways, and bridges.

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