289,159 research outputs found

    Option generation in decision making: Ideation beyond memory retrieval.

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    According to prescriptive decision theories, the generation of options for choice is a central aspect of decision making. A too narrow representation of the problem may indeed limit the opportunity to evaluate promising options. However, despite the theoretical and applied significance of this topic, the cognitive processes underlying option generation are still unclear. In particular, while a cued recall account of option generation emphasizes the role of memory and executive control, other theoretical proposals stress the importance of ideation processes based on various search and thinking processes. Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive. In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency. The criterion tasks consisted of three different poorly-structured decision-making scenarios, and the participants were asked to generate options to solve these problems. The main criterion variable of the study was the number of valid options generated, but also the diversity and the quality of generated options were examined. The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning. Thus, ideation processes, possibly supported by search and thinking processes, seem to contribute to option generation beyond basic associative memory retrieval. The findings of the study also indicate that generating more options may have multifaceted consequences for choice, increasing the quality of the best option generated but decreasing the mean quality of the options in the generated set

    Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms

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    In this talk, fitness assignment in multiobjective evolutionary algorithms is interpreted as a multi-criterion decision process. A suitable decision making framework based on goals and priorities is formulated in terms of a relational operator, characterized, and shown to encompass a number of simpler decision strategies, including constraint satisfaction, lexicographic optimization, and a form of goal programming. Then, the ranking of an arbitrary number of candidates is considered, and the effect of preference changes on the cost surface seen by an evolutionary algorithm is illustrated graphically for a simple problem. The formulation of a multiobjective genetic algorithm based on the proposed decision strategy is also discussed. Niche formation techniques are used to promote diversity among preferable candidates, and progressive articulation of preferences is shown to be possible as long as the genetic algorithm can recover from abrupt changes in the cost landscape. Finally, an application to the optimization of the low-pressure spool speed governor of a Pegasus gas turbine engine is described, which illustrates how a technique such as the Multiobjective Genetic Algorithm can be applied, and exemplifies how design requirements can be refined as the algorithm runs. The two instances of the problem studied demonstrate the need for preference articulation in cases where many and highly competing objectives lead to a non-dominated set too large for a finite population to sample effectively. It is shown that only a very small portion of the non-dominated set is of practical relevance, which further substantiates the need to supply preference information to the GA

    Multi-Criteria Performance Evaluation and Control in Power and Energy Systems

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    The role of intuition and human preferences are often overlooked in autonomous control of power and energy systems. However, the growing operational diversity of many systems such as microgrids, electric/hybrid-electric vehicles and maritime vessels has created a need for more flexible control and optimization methods. In order to develop such flexible control methods, the role of human decision makers and their desired performance metrics must be studied in power and energy systems. This dissertation investigates the concept of multi-criteria decision making as a gateway to integrate human decision makers and their opinions into complex mathematical control laws. There are two major steps this research takes to algorithmically integrate human preferences into control environments: MetaMetric (MM) performance benchmark: considering the interrelations of mathematical and psychological convergence, and the potential conflict of opinion between the control designer and end-user, a novel holistic performance benchmark, denoted as MM, is developed to evaluate control performance in real-time. MM uses sensor measurements and implicit human opinions to construct a unique criterion that benchmarks the system\u27s performance characteristics. MM decision support system (DSS): the concept of MM is incorporated into multi-objective evolutionary optimization algorithms as their DSS. The DSS\u27s role is to guide and sort the optimization decisions such that they reflect the best outcome desired by the human decision-maker and mathematical considerations. A diverse set of case studies including a ship power system, a terrestrial power system, and a vehicular traction system are used to validate the approaches proposed in this work. Additionally, the MM DSS is designed in a modular way such that it is not specific to any underlying evolutionary optimization algorithm

    Halting indigenous biodiversity decline: ambiguity, equity, and outcomes in RMA assessment of significance

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    In New Zealand, assessment of ‘significance’ is undertaken to give effect to a legal requirement for local authorities to provide for protection of significant sites under the Resource Management Act (1991). The ambiguity of the statute enables different interests to define significance according to their goals: vested interests (developers), local authorities, and non-vested interests in pursuit of protection of environmental public goods may advance different definitions. We examine two sets of criteria used for assessment of significance for biological diversity under the Act. Criteria adapted from the 1980s Protected Natural Areas Programme are inadequate to achieve the maintenance of biological diversity if ranking is used to identify only highest priority sites. Norton and Roper-Lindsay (2004) propose a narrow definition of significance and criteria that identify only a few high-quality sites as significant. Both sets are likely to serve the interests of developers and local authorities, but place the penalty of uncertainty on non-vested interests seeking to maintain biological diversity, and are likely to exacerbate the decline of biological diversity and the loss of landscape-scale processes required for its persistence. When adopting criteria for assessment of significance, we suggest local authorities should consider whose interests are served by different criteria sets, and who will bear the penalty of uncertainty regarding biological diversity outcomes. They should also ask whether significance criteria are adequate, and sufficiently robust to the uncertainty inherent in the assessment of natural values, to halt the decline of indigenous biological diversity

    A test problem for visual investigation of high-dimensional multi-objective search

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    An inherent problem in multiobjective optimization is that the visual observation of solution vectors with four or more objectives is infeasible, which brings major difficulties for algorithmic design, examination, and development. This paper presents a test problem, called the Rectangle problem, to aid the visual investigation of high-dimensional multiobjective search. Key features of the Rectangle problem are that the Pareto optimal solutions 1) lie in a rectangle in the two-variable decision space and 2) are similar (in the sense of Euclidean geometry) to their images in the four-dimensional objective space. In this case, it is easy to examine the behavior of objective vectors in terms of both convergence and diversity, by observing their proximity to the optimal rectangle and their distribution in the rectangle, respectively, in the decision space. Fifteen algorithms are investigated. Underperformance of Pareto-based algorithms as well as most state-of-the-art many-objective algorithms indicates that the proposed problem not only is a good tool to help visually understand the behavior of multiobjective search in a high-dimensional objective space but also can be used as a challenging benchmark function to test algorithms' ability in balancing the convergence and diversity of solutions

    The coastal sustainability standard: A management systems approach to ICZM

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    This paper presents a systems-based appraisal methodology that has been designed specifically to consider the effectiveness of Integrated Coastal Zone Management (ICZM) initiatives. Since ICZM is defined in terms of achieving sustainable development, any such initiative must therefore be capable of meeting the multiple and often conflicting objectives inherent in this ubiquitous concept. The methodology outlined here is designed to critically review ICZM in order to pinpoint areas of management weakness and determine the likely ‘success’ of the process. It represents an example of a management system, incorporates both qualitative and quantitative information, and is proposed as a ‘Coastal Sustainability Standard’ (CoSS). Initial field testing of the methodology has proved successful and shown that the approach holds some efficacy as a means of assessment

    Valuing Biodiversity in Life Cycle Impact Assessment

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    Erratum published on 13 March 2020, see Sustainability 2020, 12(6), 2270. https://doi.org/10.3390/su11205628In this article, the authors propose an impact assessment method for life cycle assessment (LCA) that adheres to established LCA principles for land use-related impact assessment, bridges current research gaps and addresses the requirements of different stakeholders for a methodological framework. The conservation of biodiversity is a priority for humanity, as expressed in the framework of the Sustainable Development Goals (SDGs). Addressing biodiversity across value chains is a key challenge for enabling sustainable production pathways. Life cycle assessment is a standardised approach to assess and compare environmental impacts of products along their value chains. The impact assessment method presented in this article allows the quantification of the impact of land-using production processes on biodiversity for several broad land use classes. It provides a calculation framework with degrees of customisation (e.g., to take into account regional conservation priorities), but also offers a default valuation of biodiversity based on naturalness. The applicability of the method is demonstrated through an example of a consumer product. The main strength of the approach is that it yields highly aggregated information on the biodiversity impacts of products, enabling biodiversity-conscious decisions about raw materials, production routes and end user products

    Substantive Representation of Women (and improving it). What is and should it be about?

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    More and more countries implement quotas and install women’s policy agencies as an answer to the under-representation of women and gender related interests in politics and policy. The main argument is that more women MPs and the structural presence of attention for women’s interests not only contribute to just and democratic politics, but also enhance the quality of democratic decision and policy-making on a substantive level. Women MPs and women’s policy agencies would foster the inclusion of women’s interests and gendered perspectives. However, it remains unclear what ‘substantive representation of women’ and improving it actually mean. This article first deals with the ‘what’ of substantive representation of women in terms of the acts and contents involved: what is it about? Next, it focuses on the improvement of the substantive representation of women: what is better substantive representation and how can it be reached? My answer to this question refers to quantitative improvements (e.g. more support for women’s interests) and qualitative improvements (e.g. support for more women). ‘Good’ substantive representation implies recognizing diversity and ideological conflict regarding women’s interests and gendered perspectives

    The Principles Of Developing A Management Decision Support System For Scientific Employees

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    Employees engaged in mental work have become the most valuable assets of any organization in the 21st century. The satisfaction of those involved in mental work requires the provision of objectivity and transparency in their decision-making. This, in turn, entails the development of scientifically motivated decision making mechanisms and scientific-methodological approaches to evaluate their performance based on innovative technologies.The main goal of this article is in development of the scientific and methodological framework for the establishment of a decision support system to manage the employees engaged in mental work and operating in uncertainty. In this regard, initially, the question of evaluating the activities of scientific workers is examined, its characteristic features are determined, and the fuzzy relation model is proposed as a multi-criterion issue formed in uncertainty. Taking into consideration the hierarchical structure of the criteria that allows evaluating the activities of scientific workers, a phased solution method based on an additive aggregation method is proposed. In accordance with the methodology, a functional scheme of the decision support system to manage the scientific personnel is developed. The working principle of each block and the interaction of the blocks are described. The rules for the employees\u27 management decisions are shown by referring to the knowledge production model.Based on the proposed methodological approach, the implementation phases of the decision support system for the management of the scientific workers of the Institute of Information Technology of ANAS are described. To evaluate the employees\u27 performance, the tools to collect initial information, evaluate the system of criteria, define their importance coefficients and mathematical descriptions are provided. Some results of the system software are presented. The opportunities of the system based on the proposed methodology to support enterprise mangers to make scientifically justified decisions are provided
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