Multi-Objective Planning for Ice Road Routes on Alaska's North Slope: Algorithms and Technology Development Conference Paper uri icon

abstract

  • The North Slope Decision Support System (NSDSS) is currently under development as a technology in support of oil and gas exploration and development that explicitly considers optimal water use, direct and cumulative environmental impacts, and multiple objectives and values among stakeholders. Major modules of the DSS include information systems, natural system models, and planning and management functions. Development of the DSS is a collaborative effort of academic and industry personnel with significant stakeholder involvement from multiple agencies of local, state, and federal government, private energy companies, and non-governmental organizations. Ice roads and ice pads provide a cost-effective means of oil and gas exploration with minimal impact to the sensitive underlying tundra. Consequently, these ice structures have become integral to oil and gas exploration activities on the North Slope. Their widespread use represents a challenge to water resource managers, however, due to the large volume of water required to construct and maintain them. Crucial questions on water balance and ecosystem impact must be considered in the state regulatory process that permits construction of these ice structures. NSDSS includes multi-objective planning routines for ice road routes. Pareto-optimal route alternatives are determined for cost, travel time, completion date, and other objectives. Spatial search domains are built using geographic information system (GIS) layers for a range of variables including water availability, vegetation and wildlife sensitivity, and topography, among others. Ant Colony System (ACS) optimization is utilized with novel algorithms for graph pre- and post-processing to improve solution efficiency. Output from the planning routines allows decision makers to understand tradeoff relationships among objectives. The current form of the ice road planning (IRP) algorithm will be extended to include water balance analysis to understand likely long-term impacts on regional water resources and possible adaptation measures. © 2010 ASCE.

author list (cited authors)

  • Brumbelow, K., Aryasomayaula, A. K., Bourne, S. F., & Tidwell, A. C.

citation count

  • 0

publication date

  • May 2010