scholarly journals FOX-GA: A Genetic Algorithm for Generating and Analyzing Battlefield Courses of Action

1999 ◽  
Vol 7 (1) ◽  
pp. 45-68 ◽  
Author(s):  
J. L. Schlabach ◽  
C. C. Hayes ◽  
D. E. Goldberg
Keyword(s):  
Genetic Algorithm ◽  
Decision Support ◽  
Real World ◽  
Computational Efficiency ◽  
Planning Problem ◽  
Selection Mechanism ◽  
Problem Domain ◽  
Trade Offs ◽  
Additional Challenge ◽  
Modern Warfare

This paper describes FOX-GA, a genetic algorithm (GA) that generates and evaluates plans in the complex domain of military maneuver planning. FOX-GA's contributions are to demonstrate an effective application of GA technology to a complex real world planning problem, and to provide an understanding of the properties needed in a GA solution to meet the challenges of decision support in complex domains. Previous obstacles to applying GA technology to maneuver planning include the lack of efficient algorithms for determining the fitn ess of plans. Detailed simulations would ideally be used to evaluate these plans, but most such simulations typically require several hours to assess a single plan. Since a GA needs to quickly generate and evaluate thousands of plans, these methods are too slow. To solve this problem we developed an efficient evaluator (wargamer) that uses course-grained representations of this problem domain to allow appropriate yet intelligent trade-offs between computational efficiency and accuracy. An additional challenge was that users needed a diverse set of significantly different plan options from which to choose. Typical GA's tend to develop a group of “best” solutions that may be very similar (or identical) to each other. This may not provide users with sufficient choice. We addressed this problem by adding a niching strategy to the selection mechanism to insure diversity in the solution set, providing users with a more satisfactory range of choices. FOX-GA's impact will be in providing decision support to time constrained and cognitively overloaded battlestaff to help them rapidly explore options, create plans, and better cope with the information demands of modern warfare.

scholarly journals The evolution of life cycle assessment in European policies over three decades

2021 ◽  
Author(s):  
Serenella Sala ◽  
Andrea Martino Amadei ◽  
Antoine Beylot ◽  
Fulvio Ardente
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Decision Support ◽  
General Concept ◽  
Life Cycle Thinking ◽  
Environmental Footprint ◽  
Science And Policy ◽  
Policy Domain ◽  
Trade Offs ◽  
The Eu

Abstract Purpose Life cycle thinking (LCT) and life cycle assessment (LCA) are increasingly considered pivotal concept and method for supporting sustainable transitions. LCA plays a relevant role in decision support, for the ambition of a holistic coverage of environmental dimensions and for the identification of hotspots, possible trade-offs, and burden shifting among life cycle stages or impact categories. These features are also relevant when the decision support is needed in policy domain. With a focus on EU policies, the present study explores the evolution and implementation of life cycle concepts and approaches over three decades. Methods Adopting an historical perspective, a review of current European Union (EU) legal acts and communications explicitly mentioning LCT, LCA, life cycle costing (LCC), and environmental footprint (the European Product and Organisation Environmental Footprint PEF/OEF) is performed, considering the timeframe from 1990 to 2020. The documents are categorised by year and according to their types (e.g. regulations, directives, communications) and based on the covered sectors (e.g. waste, energy, buildings). Documents for which life cycle concepts and approaches had a crucial role are identified, and a shortlist of these legal acts and communications is derived. Results and discussion Over the years, LCT and life cycle approaches have been increasingly mentioned in policy. From the Ecolabel Regulation of 1992, to the Green Deal in 2019, life cycle considerations are of particular interest in the EU. The present work analysed a total of 159 policies and 167 communications. While in some sectors (e.g. products, vehicles, and waste) life cycle concepts and approaches have been adopted with higher levels of prescriptiveness, implementation in other sectors (e.g. food and agriculture) is only at a preliminary stage. Moreover, life cycle (especially LCT) is frequently addressed and cited only as a general concept and in a rather generic manner. Additionally, more stringent and rigorous methods (LCA, PEF/OEF) are commonly cited only in view of future policy developments, even if a more mature interest in lifecycle is evident in recent policies. Conclusion The EU has been a frontrunner in the implementation of LCT/LCA in policies. However, despite a growing trend in this implementation, the development of new stringent and mandatory requirements related to life cycle is still relatively limited. In fact, there are still issues to be solved in the interface between science and policy making (such as verification and market surveillance) to ensure a wider implementation of LCT and LCA.

scholarly journals Decision support framework for the regional facility location and development planning problem

2021 ◽  
Author(s):  
David Kik ◽  
Matthias Gerhard Wichmann ◽  
Thomas Stefan Spengler
Keyword(s):  
Decision Support ◽  
Facility Location ◽  
Future Orientation ◽  
Real Life ◽  
Development Planning ◽  
Major Influence ◽  
Location Decisions ◽  
Planning Problem ◽  
Location Factor ◽  
Decision Support Framework

AbstractLocation choice is a crucial planning task with major influence on a company’s future orientation and competitiveness. It is quite complex, since multiple location factors are usually of decision-relevance, incomparable, and sometimes conflictual. Further, ongoing urbanization is associated with locational dynamics posing major challenges for the regional location management of companies and municipalities. For example, respecting urban space as location factor, a scarcity growing over time leads to different assessment and requirements on a company’s behalf. For both companies and municipalities, there is a need for location development which implies an active change of location factor characteristics. Accordingly, considering locational dynamics is vital, as they may be decisive in the location decision-making. Although certain dynamics are considered within conventional Facility Location Problem (FLP) approaches, a systematic consideration of active location development is missing so far. Consequently, they may propagate long-term unfavorable location decisions, as major potentials associated with company-driven and municipal development measures are neglected. Therefore, this paper introduces a comprehensive decision support framework for the Regional Facility Location and Development planning Problem (RFLDP). It provides an operationalization of development measures, and thus anticipates dynamic adaptations to the environment. An established multi-criteria approach is extended to this new application. A complementary guideline ensures its meaningful applicability by practitioners. Based on a real-life case study, the decision support framework’s strength for practical application is demonstrated. Here, major advantages over conventional FLP approaches are highlighted. It is shown that the proposed methodology results in alternative location decisions which are structurally superior.

scholarly journals Decision Support for the (Inter-)Basin Management of Water Resources Using Integrated Hydro-Economic Modeling

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Gerald Norbert Souza da Silva ◽  
Márcia Maria Guedes Alcoforado de Moraes
Keyword(s):  
Decision Support ◽  
Water Resources ◽  
Water Allocation ◽  
Hydrological Modeling ◽  
Well Being ◽  
Water Transfer ◽  
Economic Modeling ◽  
Trade Offs ◽  
Study Results

The development of adequate modeling at the basin level to establish public policies has an important role in managing water resources. Hydro-economic models can measure the economic effects of structural and non-structural measures, land and water management, ecosystem services and development needs. Motivated by the need of improving water allocation using economic criteria, in this study, a Spatial Decision Support System (SDSS) with a hydro-economic optimization model (HEAL system) was developed and used for the identification and analysis of an optimal economic allocation of water resources in a case study: the sub-middle basin of the São Francisco River in Brazil. The developed SDSS (HEAL system) made the economically optimum allocation available to analyze water allocation conflicts and trade-offs. With the aim of providing a tool for integrated economic-hydrological modeling, not only for researchers but also for decision-makers and stakeholders, the HEAL system can support decision-making on the design of regulatory and economic management instruments in practice. The case study results showed, for example, that the marginal benefit function obtained for inter-basin water transfer, can contribute for supporting the design of water pricing and water transfer decisions, during periods of water scarcity, for the well-being in both basins.

Motion Planning of a Nonholonomic Multibody System Using Genetic Algorithm

2003 ◽  
Author(s):  
Xin-Sheng Ge ◽  
Li-Qun Chen
Keyword(s):  
Genetic Algorithm ◽  
Motion Planning ◽  
Nonholonomic System ◽  
Multibody System ◽  
Planning Problem ◽  
Control Approach ◽  
Velocity Constraints ◽  
Nonholonomic Motion Planning ◽  
Optimal Control Approach ◽  
Motion Planning Problem

The motion planning problem of a nonholonomic multibody system is investigated. Nonholonomicity arises in many mechanical systems subject to nonintegrable velocity constraints or nonintegrable conservation laws. When the total angular momentum is zero, the control problem of system can be converted to the motion planning problem for a driftless control system. In this paper, we propose an optimal control approach for nonholonomic motion planning. The genetic algorithm is used to optimize the performance of motion planning to connect the initial and final configurations and to generate a feasible trajectory for a nonholonomic system. The feasible trajectory and its control inputs are searched through a genetic algorithm. The effectiveness of the genetic algorithm is demonstrated by numerical simulation.

Hybrid argumentation systems for structured news reports

2001 ◽  
Vol 16 (4) ◽  
pp. 295-329 ◽  
Author(s):  
ANTHONY HUNTER
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Hybrid Systems ◽  
Real World ◽  
Hybrid Approach ◽  
Graphical Notation ◽  
The Real ◽  
News Reports ◽  
Further Development ◽  
Argumentation Systems

Numerous argumentation systems have been proposed in the literature. Yet there often appears to be a shortfall between proposed systems and possible applications. In other words, there seems to be a need for further development of proposals for argumentation systems before they can be used widely in decision-support or knowledge management. I believe that this shortfall can be bridged by taking a hybrid approach. Whilst formal foundations are vital, systems that incorporate some of the practical ideas found in some of the informal approaches may make the resulting hybrid systems more useful. In informal approaches, there is often an emphasis on using graphical notation with symbols that relate more closely to the real-world concepts to be modelled. There may also be the incorporation of an argument ontology oriented to the user domain. Furthermore, in informal approaches there can be greater consideration of how users interact with the models, such as allowing users to edit arguments and to weight influences on graphs representing arguments. In this paper, I discuss some of the features of argumentation, review some key formal argumentation systems, identify some of the strengths and weaknesses of these formal proposals and finally consider some ways to develop formal proposals to give hybrid argumentation systems. To focus my discussions, I will consider some applications, in particular an application in analysing structured news reports.

scholarly journals Advanced SIMION Techniques: Boundary Matching and Genetic Optimization

2015 ◽  
Vol 21 (S4) ◽  
pp. 218-223 ◽  
Author(s):  
D. Dowsett
Keyword(s):  
Genetic Algorithm ◽  
Real World ◽  
Great Accuracy ◽  
Genetic Optimization ◽  
Real World Applications ◽  
Boundary Matching

AbstractTwo techniques for use with SIMION [1] are presented, boundary matching and genetic optimization. The first allows systems which were previously difficult or impossible to simulate in SIMION to be simulated with great accuracy. The second allows any system to be rapidly and robustly optimized using a parallelized genetic algorithm. Each method will be described along with examples of real world applications.

Beyond the Known: Detecting Novel Feasible Domains Over an Unbounded Design Space

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Wei Chen ◽  
Mark Fuge
Keyword(s):  
Real World ◽  
Adaptive Sampling ◽  
Design Space ◽  
Fundamental Problem ◽  
Domain Boundary ◽  
Sampling Technique ◽  
Standard Test ◽  
Worst Case ◽  
Trade Offs ◽  
Design Variables

To solve a design problem, sometimes it is necessary to identify the feasible design space. For design spaces with implicit constraints, sampling methods are usually used. These methods typically bound the design space; that is, limit the range of design variables. But bounds that are too small will fail to cover all possible designs, while bounds that are too large will waste sampling budget. This paper tries to solve the problem of efficiently discovering (possibly disconnected) feasible domains in an unbounded design space. We propose a data-driven adaptive sampling technique—ε-margin sampling, which learns the domain boundary of feasible designs and also expands our knowledge on the design space as available budget increases. This technique is data-efficient, in that it makes principled probabilistic trade-offs between refining existing domain boundaries versus expanding the design space. We demonstrate that this method can better identify feasible domains on standard test functions compared to both random and active sampling (via uncertainty sampling). However, a fundamental problem when applying adaptive sampling to real world designs is that designs often have high dimensionality and thus require (in the worst case) exponentially more samples per dimension. We show how coupling design manifolds with ε-margin sampling allows us to actively expand high-dimensional design spaces without incurring this exponential penalty. We demonstrate this on real-world examples of glassware and bottle design, where our method discovers designs that have different appearance and functionality from its initial design set.

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