scholarly journals Geospatial Decision-Making Framework Based on the Concept of Satisficing

2021 ◽  
Vol 10 (5) ◽  
pp. 326
Author(s):  
Goran Milutinović ◽  
Stefan Seipel ◽  
Ulla Ahonen-Jonnarth
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Interactive Visualization ◽  
Deep Understanding ◽  
Data Sets ◽  
Decision Making Framework ◽  
Decision Making Model ◽  
Decision Paths ◽  
Reduced Data ◽  
Insight Into

Decision-making methods used in geospatial decision making are computationally complex prescriptive methods, the details of which are rarely transparent to the decision maker. However, having a deep understanding of the details and mechanisms of the applied method is a prerequisite for the efficient use thereof. In this paper, we present a novel decision-making framework that emanates from the need for intuitive and easy-to-use decision support systems for geospatial multi-criteria decision making. The framework consists of two parts: the decision-making model Even Swaps on Reduced Data Sets (ESRDS), and the interactive visualization framework. The decision-making model is based on the concept of satisficing, and as such, it is intuitive and easy to understand and apply. It integrates even swaps, a prescriptive decision-making method, with the findings of behavioural decision-making theories. Providing visual feedback and interaction opportunities throughout the decision-making process, the interactive visualization part of the framework helps the decision maker gain better insight into the decision space and attribute dependencies. Furthermore, it provides the means to analyse and compare the outcomes of different scenarios and decision paths.

The Role of Philanthropy on the Strategic Planning Process of a Selective Liberal Arts and Science College

2020 ◽  
pp. 1364-1384
Author(s):  
Wayne P. Webster ◽  
Rick C. Jakeman ◽  
Susan Swayze
Keyword(s):  
Decision Making ◽  
Strategic Planning ◽  
Liberal Arts ◽  
Planning Process ◽  
Deep Understanding ◽  
Strategic Planning Process ◽  
Strategic Plans ◽  
The Future ◽  
Science College ◽  
Decision Making Model

This chapter describes how constituencies of a four-year, private liberal arts and science college perceived the effect of philanthropy on the strategic planning process. Due to their reliance upon tuition revenues and private support, liberal arts and science colleges are particularly susceptible to ebbs and flows in the economy. How these institutions plan for the future and the extent to which philanthropy factors into strategic plans provides crucial information about the future of these higher education institutions (Connell, 2006). Gaining a deep understanding of how philanthropy shapes a strategic planning process and the decision-making model that was used during the process provides insight into how philanthropy, strategic planning, and decision-making models intersect to form a new decision-making model, described as feedback and revenue.

An integrated neural network stochastic dynamic programming model for optimizing the operation policy of Aswan High Dam

2011 ◽  
Vol 42 (1) ◽  
pp. 50-67 ◽  
Author(s):  
A. H. El-Shafie ◽  
M. S. El-Manadely
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Dynamic Programming ◽  
Decision Maker ◽  
Stochastic Dynamic Programming ◽  
Programming Model ◽  
Stochastic Dynamic ◽  
Release Policy ◽  
Aswan High Dam ◽  
Decision Making Model

Developing optimal release policies of multipurpose reservoirs is very complex, especially for reservoirs within a stochastic environment. Existing techniques are limited in their ability to represent risks associated with deciding a release policy. The risk aspect of the decisions affects the design and operation of reservoirs. A decision-making model is presented that is capable of replicating the manner in which risks associated with reservoir release decisions are perceived, interpreted and compared by a decision-maker. The model is based on Neural Network (NN) theory. This decision-making model can be used with a Stochastic Dynamic Programming (SDP) approach to produce a NN-SDP model. The resulting integrated model allows the attitudes towards risk of a decision-maker to be considered explicitly in defining the optimal release policy. Clear differences in the policies generated from the basic SDP and the NN-SDP models are observed when examining the operation of Aswan High Dam (AHD). The NN-SDP model yields policies that are more reliable and resilient and less vulnerable than those obtained using the SDP model.

scholarly journals Influence Analysis in Consensus Search — A Multi Criteria Group Decision Making Approach in Environmental Management

2016 ◽  
Vol 15 (04) ◽  
pp. 791-813 ◽  
Author(s):  
Jorge Ivan Romero-Gelvez ◽  
Monica Garcia-Melon
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Similarity Measures ◽  
Decision Makers ◽  
Final Decision ◽  
Analytic Hierarchy ◽  
Decision Making Model ◽  
Environmental Decision

The environmental decision problems often are divisive, even in a technical realm, decision makers with strong personalities influence outcomes. The purpose of this study is to define and quantify the factors that affect the conservation objectives of a national natural park located in Colombia, South America adding the judgments of six decision makers with different knowledge (every decision maker is also a stakeholder representative). This paper uses a hybrid multiple criteria group decision-making model (MCDM), combining the social network analysis (SNA), analytic hierarchy process (AHP) and similarity measures to solve the consensus and anchoring problem among environmental decision makers. The SNA technique is used to build an influential network relation map among decision makers and to obtain their weights for applying a weighted AHP. Then, the final decision matrices for every decision maker are compared between them in order to identify the consensus level of the problem.

scholarly journals Model Pengambilan Keputusan Pemilihan Bibit Unggul Sapi Bali Menggunakan Metode Weighted Product

2021 ◽  
Vol 8 (5) ◽  
pp. 879
Author(s):  
Dyna Marisa Khairina ◽  
Indra Cahya Pramukti ◽  
Heliza Rahmania Hatta ◽  
Septya Maharani
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Efficient Method ◽  
Germ Plasm ◽  
Selection Process ◽  
Product Method ◽  
Bali Cattle ◽  
The Right ◽  
Decision Making Model ◽  
Selection Of

<p class="Abstrak">Kesulitan dalam mencari bibit unggul pada ternak sapi bali, menyebabkan bibit unggul yang terpilih semakin tidak produktif dalam hal penggemukan ternak. Penentuan bibit unggul pada ternak sapi bali merupakan hal yang sangat krusial bagi para pengambil keputusan yang terkait dalam hal ini adalah peternak sapi bali. Jika tidak dilakukan secara tepat dan akurat, maka pemilihan bibit unggul  pada sapi bali yang keliru seringkali mengakibatkan berbagai permasalahan. Model pengambilan keputusan dapat digunakan untuk membantu manusia khususnya peternak sapi dalam mengambil keputusan. Metode <em>Weighted Product</em> adalah metode yang sangat efektif dan efisien dalam pemilihan bibit unggul, karena waktu yang diperlukan untuk perhitungan jauh lebih singkat. Tujuan penelitian ini adalah membuat suatu model pengambilan keputusan untuk pemilihan bibit unggul terbaik pada ternak sapi bali. Adapun model pengambilan keputusan ini membantu memberikan rekomendasi kepada peternak dalam proses pemilihan bibit unggul sapi bali sebagai bahan pertimbangan dalam memilih secara tepat, akurat dan mempermudah proses pemilihan dengan keputusan terbaik.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The difficulty to look for superior seeds of Bali cattle causes the selected superior germ plasm being more unproductive in case of fattening cattle. The decision of superior seeds of Bali cattle is a crucial thing for the decision maker, related with this case is Bali cattle breeder. If it is not organized accurately, then the selection of superior seeds on the wrong bali cows often lead to various problems. Decision-making models can be used to help humans, especially cattle ranchers in making decisions. Weighted Product Method is a very effective and efficient method for selecting superior seeds, because the timing needed for calculation is much shorter. The purpose of this research is to make a model of decision making for selection superior seeds of Bali cattle. The decision-making model helps provide recommendations to farmers in the process of selecting superior bali cattle seeds as a material consideration in choosing the right, accurate and simplify the selection process with the best decision.</em></p><p class="Abstrak"><em><strong><br /></strong></em></p>

scholarly journals A Behavioral Decision Model Based on Fuzzy Targets in Decision Making Using Weather Information

2008 ◽  
Vol 12 (5) ◽  
pp. 435-442 ◽  
Author(s):  
Akio Hiramatsu ◽  
◽  
Van-Nam Huynh ◽  
Yoshiteru Nakamori
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Model ◽  
Weather Forecasts ◽  
Weather Information ◽  
Behavioral Decision ◽  
Psychological Features ◽  
Decision Making Model ◽  
Personal Philosophy ◽  
Fuzzy Target

Due to inevitable uncertainty in weather forecasts, many decision problems influenced by weather information have been formulated for decision making in uncertain situations. The fuzzy target-based decision making model we propose assumes that the decision maker assesses a fuzzy target expressing an aspiration, then selects the decision maximizing the possibility of attaining this target aspiration before making a decision. We then show that the decision maker's different behavior about the aspiration leads to different decisions depending on the decision maker's personal philosophy or experience. This behavioral analysis provides an interpretation for influencing psychological features of the decision maker in decision making and introduces an interesting link to attitudes towards risk by means of utility function.

scholarly journals Interrelated Decision-Making Model for Diabetes

2021 ◽  
Vol 10 (02) ◽  
pp. 170-186
Author(s):  
Normadiah Mahiddin ◽  
Zulaiha Ali Othman ◽  
Nur Arzuar Abdul Rahim
Keyword(s):  
Decision Making ◽  
Prediction Models ◽  
Forecast Accuracy ◽  
Forecast Model ◽  
Data Sets ◽  
Dynamic Prediction ◽  
Data Set ◽  
Care Level ◽  
Levels Of Care ◽  
Decision Making Model

Diabetes is one of the growing chronic diseases. Proper treatment is needed to produce its effects. Past studies have proposed an Interrelated Decision-making Model (IDM) as an intelligent decision support system (IDSS) solution for healthcare. This model can provide accurate results in determining the treatment of a particular patient. Therefore, the purpose of this study is to develop a diabetic IDM to see the increased decision-making accuracy with the IDM concept. The IDM concept allows the amount of data to increase with the addition of data records at the same level of care, and the addition of data records and attributes from the previous or subsequent levels of care. The more data or information, the more accurate a decision can be made. Data were developed to make diagnostic predictions for each stage of care in the development of type 2 diabetes. The development of data for each stage of care was confirmed by specialists. However, the experiments were performed using simulation data for two stages of care only. Four data sets of different sizes were provided to view changes in forecast accuracy. Each data set contained 2 data sets of primary care level and secondary care level with 4 times the change of the number of attributes from 25 to 58 and the number of records from 300 to 11,000. Data were developed to predict the level of diabetes confirmed by specialist doctors. The experimental results showed that on average, the J48 algorithm showed the best model (99%) followed by Logistics (98%), RandomTree (95%), NaiveBayes Updateable (93%), BayesNet (84%) and AdaBoostM1 (67%). Ratio analysis also showed that the accuracy of the forecast model has increased up to 49%. The MAPKB model for the care of diabetes is designed with data change criteria dynamically and is able to develop the latest dynamic prediction models effectively.v

The Role of Philanthropy on the Strategic Planning Process of a Selective Liberal Arts and Science College

2016 ◽  
pp. 228-255 ◽  
Author(s):  
Wayne P. Webster ◽  
Rick C. Jakeman ◽  
Susan Swayze
Keyword(s):  
Decision Making ◽  
Strategic Planning ◽  
Liberal Arts ◽  
Planning Process ◽  
Deep Understanding ◽  
Strategic Planning Process ◽  
Strategic Plans ◽  
The Future ◽  
Science College ◽  
Decision Making Model

This chapter describes how constituencies of a four-year, private liberal arts and science college perceived the effect of philanthropy on the strategic planning process. Due to their reliance upon tuition revenues and private support, liberal arts and science colleges are particularly susceptible to ebbs and flows in the economy. How these institutions plan for the future and the extent to which philanthropy factors into strategic plans provides crucial information about the future of these higher education institutions (Connell, 2006). Gaining a deep understanding of how philanthropy shapes a strategic planning process and the decision-making model that was used during the process provides insight into how philanthropy, strategic planning, and decision-making models intersect to form a new decision-making model, described as feedback and revenue.

scholarly journals Learning Representations by Humans, for Humans

2019 ◽  
Author(s):  
Sophie Hilgard ◽  
Nir Rosenfeld ◽  
Mahzarin R. Banaji ◽  
Jack Cao ◽  
David Parkes
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Decision Maker ◽  
Complementary Approach ◽  
Human Decision ◽  
Classification Tasks ◽  
Decision Making Model

We propose a new, complementary approach to interpretability, in which machines are not considered as experts whose role it is to suggest what should be done and why, but rather as advisers. The objective of these models is to communicate to a human decision-maker not what to decide but how to decide. In this way, we propose that machine learning pipelines will be more readily adopted, since they allow a decision-maker to retain agency. Specifically, we develop a framework for learning representations by humans, for humans, in which we learn representations of inputs (‘advice’) that are effective for human decision-making. Representation generating models are trained with humans-in-the-loop, implicitly incorporating the human decision-making model. We show that optimizing for human decision-making rather than accuracy is effective in promoting good decisions in various classification tasks while inherently maintaining a sense of interpretability.

scholarly journals A Satisficing Heuristic Decision-Making Model under Limited Attention and Incomplete Preferences

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xinlin Wu ◽  
Daoxin Ding
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Choice Theory ◽  
Time Pressure ◽  
Choice Model ◽  
Incomplete Preferences ◽  
Limited Attention ◽  
Limited Information ◽  
Choice Procedure ◽  
Decision Making Model

Classical choice theory assumes that a decision-maker considers all feasible alternatives. However, a decision-maker in the real world can not consider all alternatives because of limited attention. In this paper, we propose a satisficing choice model to describe the choice procedure based on the incomplete preferences under the limited attention of the decision-maker. Moreover, the existence and rationality properties of the satisficing choice model on the different domains are studied combined with some proposed rationality conditions. Further, the proposed satisficing choice model is applied to a case of quality competition. Results show that the satisficing choice model of this paper is of a certain theoretical guiding significance to a kind of emergency decisions made by decision-makers under the circumstance of time pressure and limited information. It can also be the theoretical foundation for the study on the boundedly rational decision-making.

scholarly journals People learn other people's preferences through inverse decision-making

2017 ◽  
Author(s):  
Alan Jern ◽  
Christopher Lucas ◽  
Charles Kemp
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Makers ◽  
Specific Item ◽  
Decision Making Model

People are capable of learning other people's preferences by observing the choices they make. We propose that this learning relies on inverse decision-making -- inverting a decision-making model to infer the preferences that led to an observed choice. In Experiment 1, participants observed 47 choices made by others and ranked them by how strongly each choice suggested that the decision maker had a preference for a specific item. An inverse decision-making model generated predictions that were in accordance with participants' inferences. Experiment 2 replicated and extended a previous study by Newtson (1974) in which participants observed pairs of choices and made judgments about which choice provided stronger evidence for a preference. Inverse decision-making again predicted the results, including a result that previous accounts could not explain. Experiment 3 used the same method as Experiment 2 and found that participants did not expect decision makers to be perfect utility-maximizers.

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