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utility-functions AND THE ORDER TYPE OF THE CONTINUUM

JOURNAL OF MATHEMATICAL ECONOMICS 1994年第4期23卷 387-390页

作者： BEARDON, AF MEHTA, GB UNIV QUEENSLAND ST LUCIAQLD 4067AUSTRALIA

Debreu proved that there exists a continuous isotone real-valued function on any given second countable topological pre-ordered space. It is shown that this result implies and is implied by Cantor's Theorem charac... 详细信息

关键词： utility functions ORDER TYPE LINEAR CONTINUUM

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utility functions as Aggregation functions in Face Recognition

Utility Functions as Aggregation Functions in Face Recogniti...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Dolecki, Michal Karczmarek, Pawel Kiersztyn, Adam Pedrycz, Witold John Paul II Catholic Univ Lublin Inst Math & Comp Sci Ul Konstantynow 1H PL-20708 Lublin Poland Univ Alberta Dept Elect & Comp Engn Edmonton AB T6R 2V4 Canada King Abdulaziz Univ Dept Elect & Comp Engn Jeddah 21589 Saudi Arabia Polish Acad Sci Syst Res Inst Warsaw Poland

ISBN: (纸本)9781509042401

Face recognition by computers in recent years has been a topic of intensive studies. In this problem, we witness several challenges: one has to cope with large data sets, solve problems of data extraction, and deal with poor quality of images caused by e.g., poor lighting of the subject. There have been a lot of algorithms and classifiers developed, which are aimed at recognizing faces of individuals. In this paper, we present a novel classification method, which involves a collection of classifiers with a certain utility function regarded as an aggregation operator. The nearest neighbor method with various similarity measures is used as a generic classifier for selected face areas. The main task is to assign photos of a person to one of the classes of image present in the available database. This problem is similar to the decision-making process with some evident analogies. If in face recognition, a single classifier is being used, the problem becomes similar to the one of decision-making with a single criterion. When having several classifiers, the problem resembles a problem of a multi-criteria decision making. The second scenario requires an aggregation of the results produced by different classifiers. The paper presents the use of the utility function which is well-known in the decision-making theory as an aggregation operator applied to the results of various classifiers. The study is focused on the two-factor utility function and its variants.

关键词： face recognition aggregation functions utility functions

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The efficacy of utility functions for multicriteria hospital case-mix planning

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第2期31卷 807-862页

作者： Burdett, Robert L. Corry, Paul Yarlagadda, Prasad Cook, David Birgan, Sean Queensland Univ Technol Sch Math Sci Brisbane Qld 4001 Australia Univ Southern Queensland Toowoomba Qld 4350 Australia Princess Alexandra Hosp 2 Ipswich Rd Woolloongabba Qld 4102 Australia

A new approach to perform hospital case-mix planning (CMP) is introduced in this article. Our multicriteria approach utilizes utility functions (UF) to articulate the preferences and standpoint of independent decision makers regarding outputs. The primary aim of this article is to test whether a utility functions method (UFM) based on the scalarization of aforesaid UF is an appropriate quantitative technique to (i) distribute hospital resources to different operating units and (ii) provide a better capacity allocation and case mix. Our approach is motivated by the need to provide a method able to evaluate the trade-off between different stakeholders and objectives of hospitals. To the best of our knowledge, no such approach has been considered before in the literature. As we will later show, this idea addresses various technical limitations, weaknesses, and flaws in current CMP. The efficacy of the aforesaid approach is tested on a case study of a large tertiary hospital. Currently UF are not used by hospital managers, and real functions are unavailable, hence, 14 rational options are tested. Our exploratory analysis has provided important guidelines for the application of these UF. It indicates that these UF provide a valuable starting point for planners, managers, and executives of hospitals to impose their goals and aspirations. In conclusion, our approach may be better at identifying case mix that users want to treat and seems more capable of modeling the varying importance of different levels of output. Apart from finding desirable case mixes to consider, the approach can provide important insights via a sensitivity analysis of the parameters of each UF.

关键词： hospital capacity analysis hospital case-mix planning utility functions multicriteria achievement scalarizing function OR in health services

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Fuzzy UTASTAR: A method for discovering utility functions from fuzzy data

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第12期38卷 15463-15474页

作者： Patiniotakis, Ioannis Apostolou, Dimitris Mentzas, Gregoris Natl Tech Univ Athens Athens 15780 Greece Univ Piraeus Dept Informat Piraeus 18534 Greece

We propose Fuzzy UTASTAR, a method for inferring fuzzy utility functions from a partial preorder of options evaluated on multiple criteria. It is an extension of the well-known UTASTAR method capable to handle both ordinary (crisp) and fuzzy evaluation data. This property gives much flexibility to decision makers because the majority of real-life decision problems involve a considerable level of uncertainty that hinders them from assigning exact evaluations (scores) to options. In case all evaluation data are crisp the method behaves exactly as the original UTASTAR. The proposed method builds fuzzy additive value functions taking as input a partial preorder on a subset of the options, called reference set, along with their associated scores on the criteria. The resulting fuzzy utility functions can subsequently be used to estimate the (fuzzy) utility of each option, thus allowing their ranking, prioritization, selection or classification. The ranking of the options in partial preorder is as compatible as possible to the original one. The method is implemented into a decision support system and is applied to an example from the transportation domain. Results are found to be in concordance with those of the original method. To the best of our knowledge this is the first attempt to extend UTASTAR method to handle both crisp and fuzzy evaluation data. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： UTASTAR Multiple criteria decision making utility functions Fuzzy numbers Fuzzy linear programming

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Existence, uniqueness, and determinacy of a nonnegative equilibrium price vector in asset markets with general utility functions and an elliptical distribution

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2004年第3期21卷 393-405页

作者： Chen, ZP Xian Jiaotong Univ Fac Sci Dept Comp Sci & Appl Software Xian 710049 Peoples R China

For the asset market with finite numbers of investors whose utility functions are general concave functions, we derive a necessary and sufficient condition for the existence and uniqueness of the nonnegative equilibrium price vector that clears the asset market, through considering the expected utility maximization problem under the assumption that the joint distribution of risky assets' returns is an elliptical distribution. An explicit formula for the equilibrium price is given. We also discuss the economic implication of the given condition and demonstrate that our necessary and sufficient condition can be regarded as a necessary condition to maintain the stability of the asset market. These results extend some results about the equilibrium analysis of the asset market.

关键词： equilibrium prices the asset market utility functions the elliptical distribution optimal portfolios economic implication

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The impact of Chinese airport infrastructure on airline pollutant emissions: A hybrid stochastic-neural network approach based on utility functions

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 352卷 120117页

作者： Cui, Qiang Antunes, Jorge Wanke, Peter Tan, Yong Roubaud, David Jabbour, Charbel Jose Chiappetta Southeast Univ Sch Econ & Management Nanjing 211189 Peoples R China Univ Fed Rio de Janeiro Rio De Janeiro Brazil Univ Bradford Sch Management Bradford England Montpellier Business Sch Montpellier France Woxsen Univ Sch Business Hyderabad India NEOMA Business Sch Paris France

With China being the world's largest emitter of greenhouse gases and its aviation sector burgeoning, the environmental performance of Chinese airlines has global significance. Amidst rising demands for eco-friendly practices from both customers and regulators, the interplay between airport infrastructure and environmental performance becomes pivotal. This research offers an innovative methodology to gauge the environmental performance of Chinese airlines, emphasizing the distance traveled between airports using weighted additive utility functions. Leveraging neural networks, the study investigates the impact of various airport infrastructural characteristics on environmental performance. Noteworthy findings indicate that ground control measures, automatic information services at origin airports, surface concrete on runways at both ends, and a centerline lighting system in destination airports positively influence environmental performance. In contrast, longer and wider runways at origin airports, increased distances to control towers, and asphalt runways at destination airports adversely affect it. These insights not only underscore the importance of strategic infrastructure enhancements for reducing carbon footprints but also hold profound policy implications. As global climate change remains at the forefront, fostering sustainable airport infrastructure in China can significantly contribute to worldwide mitigation efforts.

关键词： Air transport industry China Environmental performance index utility functions Distance traveled Neural networks

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Optimal resource allocation in multi-class networks with user-specified utility functions

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COMPUTER NETWORKS 2002年第5期38卷 613-630页

作者： Kalyanasundaram, S Chong, EKP Shroff, NB Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Motorola Inc Global Telecom Solut Sector Arlington Hts IL USA Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA

In this work, we consider the problem of resource allocation in multi-class networks, where users specify the value they attach to obtaining different amounts of resource by means of a utility function. We develop a resource allocation scheme that maximizes the average aggregate utility per unit time. We formulate this resource allocation problem as a Markov decision process. We present numerical results that illustrate that our scheme performs better than the greedy resource allocation policy. We also discuss the implications of deliberate lying by users about their utility functions and develop a pricing scheme that prevents such lying. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： resource allocation pricing Markov decision processes utility functions greedy scheme complete partitioning

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Analytical framework for multiuser uplink MEMO space-time scheduling design with convex utility functions

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2004年第5期3卷 1832-1843页

作者： Lau, KN Hong Kong Univ Sci & Technol Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China

In this paper, we derive a novel analytical framework for designing optimal multiple-input multiple-output (MIMO) uplink space-time scheduling algorithms with respect to general convex utility functions. The novel approach we take is to discretize the search space and apply integer-programming techniques. We assume that mobile terminal has n(T) transmit antennas while the base station has n(R) receive antennas. With multiple antennas at the transmitter and the receiver, joint beam-forming has to be considered. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we impose a linear spatial processing constraint at the physical layer of the base station. We apply the framework to two commonly used system utility functions, namely, maximal throughput and proportional fair. We devise an optimal scheduling algorithm based on our framework as a performance reference and observe that transmit antennas and receive antennas have different roles in the system performance. On the other hand, we study how far we are from the optimal performance on a widely used heuristic called the greedy algorithm in 3G1x and Universal Mobile Terrestrial Service (UMTS) systems. We found that it is optimal when n(R) = 1 but there is quite a large performance penalty when n(R) > 1 compared with the optimal reference. We further propose another heuristic algorithm [called the genetic algorithm(GA)] and found that the GA is quite promising in terms of performance complexity tradeoff, especially for large K (number of mobile users), n(T), and n(R).

关键词： genetic algorithm multiple antenna multiple-input multiple-output (MIMO) scheduling optimal algorithm proportional fairness utility functions

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Achieving self-management via utility functions

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IEEE INTERNET COMPUTING 2007年第1期11卷 40-+页

作者： Kephart, Jeffrey O. Das, Rajarshi IBM Corp TJ Watson Res Ctr Armonk NY 10504 USA

Self-management in accordance with high-level objectives that users can specify is a hallmark of autonomic computing systems. The authors advocate utility functions as a principled, practical, and general way of representing such objectives. In an effort to bring the promise of utility-based frameworks to the marketplace, they describe how they've implemented them in two commercial products so as to achieve efficient resource allocation in a prototype data center. They also address several challenges to commercialization stemming from the need to reconcile the two products' fundamentally different types of objectives.

关键词： Resource Allocation utility Programs Self Management utility Function Autonomic Computing System Resource Allocation Prototype Data Center Computer Vision Resource Management Humans Prototypes Commercialization Distributed Computing Artificial Intelligence Proposals Design Optimization Control System Synthesis Autonomic Computing utility functions

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Modeling cloud business customers' utility functions

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 105卷 737-753页

作者： Wu, Caesar Buyya, Rajkumar Ramamohanarao, Kotagiri Univ Melbourne Sch Comp & Informat Syst CLOUDS Lab Melbourne Vic 3010 Australia

Modeling a utility function for cloud business customers is one of the critical challenges facing many cloud service providers (CSPs) for their pricing strategy. It concerns how to measure various subjective experiences of the business customers and how to translate their cloud service experiences into a quantifiable unit, which can be determined by a utility function that reflects cloud resource consumption. The aim of this modeling process is to set up a pricing foundation so that CSPs can target a broader range of customers from various market segments and identify the optimal price point of their various pricing models. Previous studies have either focused on simple theoretical proof or drifted the meaning of utility between demand and supply or proposed a solution based on a uniform cloud market assumption. This paper proposes a novel and practical solution to define multiple utility functions based on a scenario of six cloud market segments, which are analyzed by three analytic approaches that are known as Markov chains analysis, queueing theory, and risk assessment. The entire pricing strategy emphasizes value co-creation between CSP and cloud business customers. In comparison with other methods, such as calibrated, price-quality, resource-based, simple linear, and capacity-aware, this method provides both internal and external rationalities for CSP to capture the subjective value of cloud business customers. Consequently, our experiment results show that this modeling method can increase a profit margin by 51% and decrease a unit cost by 22% for a CSP. (C) 2020 Elsevier B.V. All rights reserved.

关键词： utility functions Creation with cloud customers Cloud market segment Business customers Value co-creation Business application Cloud service provider

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