Asset Protection - Explore the Science & Experts | ideXlab

Scan Science and Technology

Contact Leading Edge Experts & Companies

Asset Protection

The Experts below are selected from a list of 2061 Experts worldwide ranked by ideXlab platform

Jd Ike Devji – 1st expert on this subject based on the ideXlab platform

  • Physician Asset Protection: 5 practical lessons
    , 2019
    Co-Authors: Jd Ike Devji

    Abstract:

    An examination of Asset Protection issues from current news headlines highlights the defensive measures doctors and healthcare executives must consider.

  • Physician Asset Protection Failures in the News
    , 2018
    Co-Authors: Jd Ike Devji

    Abstract:

    Recent news headlines have featured catastrophic Asset Protection planning failures by doctors and their legal counsel.

  • Understanding Your Asset Protection Plan
    , 2017
    Co-Authors: Jd Ike Devji

    Abstract:

    Outside of a basic set of best practices and common risks, Asset Protection plans are as fact specific as the care you give your patients.

Sarah Kammer – 2nd expert on this subject based on the ideXlab platform

  • LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. Home.
    , 2016
    Co-Authors: Sarah Kammer

    Abstract:

    LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. Home.

  • LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. 9:00 a.m. – Kick Off and History.
    , 2016
    Co-Authors: Sarah Kammer

    Abstract:

    LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. 9:00 a.m. – Kick Off and History.

  • LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. Library Resources for Further Study on Symposium Topic.
    , 2016
    Co-Authors: Sarah Kammer

    Abstract:

    LibGuides. Asset Protection and Trust Innovations: South Dakota’s Role in Paving the Way for Innovations Nationwide – Spring 2016 Law Review Symposium. Library Resources for Further Study on Symposium Topic.

John W Hearne – 3rd expert on this subject based on the ideXlab platform

  • a spatial decomposition based math heuristic approach to the Asset Protection problem
    Operations Research Perspectives, 2020
    Co-Authors: Dian Nuraiman, Melih Ozlen, John W Hearne

    Abstract:

    Abstract This paper addresses the highly critical task of planning Asset Protection activities during uncontrollable wildfires known in the literature as the Asset Protection Problem (APP). In the APP each Asset requires a protective service to be performed by a set of emergency response vehicles within a specific time period defined by the spread of fire. We propose a new spatial decomposition based math-heuristic approach for the solution of large-scale APP’s. The heuristic exploits the property that time windows are geographically correlated as fire spreads across a landscape. Thus an appropriate division of the landscape allows the problem to be decomposed into smaller more tractable sub-problems. The main challenge then is to minimise the difference between the final locations of vehicles from one division to the optimal starting locations of the next division. The performance of the proposed approach is tested on a set of benchmark instances from the literature and compared to the most recent Adaptive Large Neighborhood Search (ALNS) algorithm developed for the APP. The results show that our proposed solution approach outperforms the ALNS algorithm on all instances with comparable computation time. We also see a trend with the margin of out-performance becoming more significant as the problems become larger.

  • a two stage stochastic approach for the Asset Protection problem during escaped wildfires with uncertain timing of a wind change
    arXiv: Optimization and Control, 2018
    Co-Authors: Iman Roozbeh, John W Hearne, Babak Abbasi, Melih Ozlen

    Abstract:

    Wildfires are natural disasters capable of damaging economies and communities. When wildfires become uncontrollable, Incident Manager Teams (IMT’s) dispatch response vehicles to key Assets to undertake protective tasks and so mitigate the risk to these Assets. In developing a deployment plan under severe time pressure, IMT’s need to consider the special requirements of each Asset, the resources (vehicles and their teams), as well as uncertainties associated with the wildfire. A common situation that arises in southern Australian wildfires is a wind change. There is a reliable forecast of a wind change, but some uncertainty around the timing of that change. To assist IMT’s to deal with this situation we develop a two-stage stochastic model to integrate such an uncertainty with the complexities of Asset Protection operations. This is the first time a mathematical model is proposed which considers uncertainty in the timing of a scenario change. The model is implemented for a case study that uses the context of the 2009 Black Saturday bushfires in Victoria. A new set of benchmark instances is generated using realistic wildfire attributes to test the computational tractability of our model and the results compared to a dynamic rerouting approach. The computations reveal that, compared with dynamic rerouting, the new model can generate better deployment plans. The model can achieve solutions in operational time for realistic-sized problems, although for larger problems the sub-optimal rerouting algorithm would still need to be deployed.

  • an adaptive large neighbourhood search for Asset Protection during escaped wildfires
    Computers & Operations Research, 2018
    Co-Authors: Iman Roozbeh, Melih Ozlen, John W Hearne

    Abstract:

    Abstract The Asset Protection problem is encountered where an uncontrollable fire is sweeping across a landscape comprising important infrastructure Assets. Protective activities by teams of firefighters can reduce the risk of losing a particular Asset. These activities must be performed during a time-window for each Asset determined by the progression of the fire. The nature of some Assets is such that they require the simultaneous presence of more than one fire vehicle and its capabilities must meet the requirements of each Asset visited. The objective is then to maximise the value of the Assets protected subject to constraints on the number and type of fire trucks available. The solution times to this problem using commercial solvers preclude their use for operational purposes. In this work we develop an Adaptive Large Neighbourhood Search algorithm (ALNS) based on problem-specific attributes. Several removal and insertion heuristics, including some new algorithms, are applied. A new benchmark set is generated by considering the problem attributes. In tests with small instances the ALNS is shown to achieve optimal, or near optimal, results in a fraction of the time required by CPLEX. In a second set of experiments comprising larger instances the ALNS was able to produce solutions in times suitable for operational purposes. These solutions mean that significantly more Assets can be protected than would be the case otherwise.