Hussein Abbass

Publications (4)0 Total impact

• Source

  Available from: arxiv.org

  Article: Robustness and Adaptiveness Analysis of Future Fleets

  Slawomir Wesolkowski, Michael Mazurek, James M. Whitacre, Axel Bender, Hussein Abbass
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  ABSTRACT: Making decisions about the structure of a future military fleet is a challenging task. Several issues need to be considered such as the existence of multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future might hold. It is uncertain what future events might be encountered; how fleet design decisions will influence and shape the future; and how present and future decision makers will act based on available information, their personal biases regarding the importance of different objectives, and their economic preferences. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different classes of uncertainty are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present clear risks to the fleet. We call this the analysis of a fleet's strategic positioning. This paper introduces how strategic positioning can be evaluated using computer simulations. Our main aim is to introduce a framework for capturing information that can be useful to a decision maker and for defining the concepts of robustness and adaptiveness in the context of future fleet design. We demonstrate our conceptual framework using simulation studies of an air transportation fleet. We capture uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions, different model assumptions, and different economic preferences. Proposed changes to a fleet are then analysed based on their influence on the fleet's robustness, adaptiveness, and risk to different scenarios.
  07/2009;
• Source

  Available from: arxiv.org

  Article: Computational Scenario-based Capability Planning

  Hussein Abbass, Axel Bender, Helen Dam, Stephen Baker, James M. Whitacre, Ruhul Sarker
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  ABSTRACT: Scenarios are pen-pictures of plausible futures, used for strategic planning. The aim of this investigation is to expand the horizon of scenario-based planning through computational models that are able to aid the analyst in the planning process. The investigation builds upon the advances of Information and Communication Technology (ICT) to create a novel, flexible and customizable computational capability-based planning methodology that is practical and theoretically sound. We will show how evolutionary computation, in particular evolutionary multi-objective optimization, can play a central role - both as an optimizer and as a source for innovation. Comment: GECCO-2008, Atlanta, GA, USA
  07/2009;
• Chapter: A Scenario-based Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities

  Stephen Baker, Axel Bender, Hussein Abbass, Ruhul Sarker
  04/2007: pages 485-511;
• Source

  Available from: asor.asn.au

  Article: Identifying the fleet mix in a military setting

  Hussein Abbass, Stephen Baker, Axel Bender, Ruhul Sarker
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  ABSTRACT: When assessing land vehicle fleet capabilities in off-shore military operations, it is necessary to develop and apply a reliable mechanism for creating and testing different fleet structures. In this paper, we introduce a vehicle fleet mix problem under military environment, discuss the complexity of the problem and present a fleet-optimization system for deciding an appropriate vehicle fleet mix by optimizing multiple objectives while satisfying the system constraints. The system is based on a number of heuristics that can answer a number of key questions required for long term capability planning such as utilization of current fleet, mix of different vehicle and modular units for a given scenario, and overall fleet structure. We demonstrate the effectiveness of our system through a case study based on a simple example dataset.
  01/2006;