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IEEE International Conference on System, Man, and Cybernetic

作者： Guo, Peijun Tanaka, Hideo Yokohama Natl Univ Fac Business Adm 79-4 Tokiwadai Yokohama Kanagawa 2408501 Japan Hiroshima Int Univ Fac Psychol Sci Higashihiroshima 7392695 Japan

ISBN: (纸本)9781424423835

In recent years, dealing with uncertainty using interval probabilities is receiving considerable attention by researchers. Most of researches related to interval probabilities, such as combination, marginalization, condition, Bayesian inferences, assume interval probabilities are known. How to elicit interval probabilities from subject is a basic problem for the applications of interval probability theory and till now a computational challenge. In this research, the approaches for estimating interval probabilities are proposed with the pair-wise comparison of the possible outcomes to know which one is more likely to occur. The first method is LP-based one. The second method is QP-based one. Interval expectation, interval entropy are investigated. The decision criteria under interval probabilities are given.

关键词： AHP decision analysis interval probabilities linear programming problem quadratic programming problem

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Maximum Lifetime Coverage problems with Battery Recovery Effects

Maximum Lifetime Coverage Problems with Battery Recovery Eff...

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IEEE Global Communications Conference (GLOBECOM)

作者： Fu, Norie Suppakitpaisarn, Vorapong Kimura, Kei Kakimura, Naonori Natl Inst Informat Chiyoda Ku 2-1-2 Hitotsubashi Tokyo 1018430 Japan JST ERATO Kawarabayashi Large Graph Project Tokyo Japan Univ Tokyo Dept Math Informat Tokyo 1138654 Japan Univ Tokyo Grad Sch Arts & Sci Tokyo 1138654 Japan

ISBN: (纸本)9781479935123

Scheduling sensors to prolong the lifetime of covering targets in the field is one of the central problems in wireless sensor networks. This problem, called the maximum lifetime coverage problem (MLCP), can be formulated as a linear programming problem with exponential size, and has a constant-factor approximation algorithm. In reality, however, batteries of sensors have recovery effects, which is a phenomenon that the deliverable energy in batteries can be replenished by itself if it is left idling for sufficient duration. Thanks to that effects, we can obtain much longer lifetime of sensors if each sensor is forced to take a sleep at some interval. In this paper, we introduce two models that extend the MLCP, incorporating battery recovery effects. The first model represents battery recovery effects in a deterministic way, while the second one uses a probabilistic model to imitate the effects. We then propose efficient algorithms that work for both models by extending approximation algorithms for the original MLCP. Numerical experiments show that the lifetime of our schedule is 10-40% longer than one without battery recovery effects.

关键词： approximation theory linear programming telecommunication scheduling wireless sensor networks MLCP battery recovery effect constant-factor approximation algorithm linear programming problem maximum lifetime coverage problem probabilistic model sensor scheduling wireless sensor network Approximation algorithms Approximation methods Batteries Heuristic algorithms Mathematical model Numerical models Schedules

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Off-Grid Integrated Renewable Energy System Scheduling for an un-electrified remote area 8

Off-Grid Integrated Renewable Energy System Scheduling for a...

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8th IEEE Power India International Conference (PIICON)

作者： Pathak, Dixitkumar P. Khatod, Dheeraj Kumar Indian Inst Technol Roorkee Alternate Hydro Energy Ctr Roorkee 247667 Uttarakhand India Indian Inst Technol Roorkee Dept Elect Engn Roorkee 247667 Uttarakhand India

ISBN: (纸本)9781538673393

The optimum utilization of alternative sources of energy are allied with supply of electrical power to the elected area of customers underneath grid connected or standalone mode. An alternative source of energy supports the high reliability in on-site generation. Consequently, it is found many hybrid schemes all ready existence like micro wind turbine, SPV panels, Small hydro, Biomass energy and Biogas energy systems. Moreover integrated renewable energy system (IRES) is further effective in comparison to grid extension which is too expensive. The representation of IRES provides support to specific site which is located on the nearly accessible Non-conventional energy resources and load requirement. This article reveal that an optimal modeling of MHP, solar, bio-mass, wind and bio-gas energy scheme for un-electrified remote area in Gujarat. Considering this, the seven un-electrified clusters of villages in taluka, Limkheda and district, Dahod in Gujarat state have been selected as study region. The best possible daily scheduling approach for renewable energy sources (RES) like solar, wind, small hydro, biomass, and biogas system with using battery set storage system has been proposed in this paper. The proposed IRES model has been proposed that is more economical in terms of operating cost. The proposed model has been optimized using Primal- Dual Interior Point (PDIP) method in linear programming problem (LPP) technique. The proposed representation has been verified in MATLAB environment.

关键词： Hydro SPV Biomass Wind Biogas linear programming problem

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Improving the consistency of incomplete hesitant multiplicative preference relation

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OPSEARCH 2019年第1期56卷 324-343页

作者： Sahu, Mamata Gupta, Anjana Delhi Technol Univ Dept Appl Math Delhi 110042 India

As it know, most decision processes are depends on preference relations as in the forms by comparing different alternatives over criteria. In the process of decision making, a decision maker may give his/her judgement by means of hesitant multiplicative preference relation (HMPR) using the scale of 1/9-9 for hesitancy and uncertainty. Shortage of of time, experience and lack of the experts' professional knowledge lead to form an incomplete hesitant multiplicative preference relation. In this paper we have defined a multiplicative transitive property of HMPR that preserves the hesitancy property. Another aim of this paper is to characterise two different approaches to calculate the missing element of incomplete HMPR from the incomplete one. The first approach involves two step, estimating step calculate the initial values of the missing element and the adjusting step minimizing the error. A linear programming model is developed in the second approach to calculate the missing values of incomplete hesitant multiplicative preference relation. The satisfaction degree and the acceptable consistency of complete HMPR is also checked. The whole procedure is explained with a suitable example.

关键词： Multiplicative preference relation Hesitant multiplicative preference relation Hesitant multiplicative element linear programming problem Satisfaction degree Acceptable consistency

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Maximum Transportation Throughput of Automated Guided Vehicle System by use of Models of Traffic Capacity and Traffic Capacity Consumption 3

Maximum Transportation Throughput of Automated Guided Vehicl...

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3rd SICE International Symposium on Control Systems (SICE ISCS)

作者： Kumagai, Kenji Sawada, Kenji Shin, Seiichi Univ Electrocommun Dept Mech Engn & Intelligent Syst Tokyo Japan Murata Machinery Ltd Div Res & Dev Yokohama Kanagawa Japan

ISBN: (纸本)9784907764548

This paper obtains a theoretical value of the maximum transportation throughput of Automated Guided Vehicle (AGV) System in a logistics center. To know the maximum transportation throughput is important to design the system since we need to know the feasibility of the design. It is proposed that the method which the problem to obtain the maximum transportation throughput is reduced to a linear programming problem with in this paper. This method must enable to obtain the theoretical values of large systems in shorter period of time than previous methods. We modeled that a rail have a traffic capacity, and AGVs consume the traffic capacity when they run or wait for loading or unloading. Then these relationship is used as constraints of a linear programming problem whose objective is to maximize the transportation throughput.

关键词： AGV maximum transportation throughput linear programming problem

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A Study on Controlled Node Sized Network Clustering for Unweighted Network Data 10

A Study on Controlled Node Sized Network Clustering for Unwe...

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Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) / 19th International Symposium on Advanced Intelligent Systems (ISIS)

作者： Nakano, Shusuke Hamasuna, Yukihiro Endo, Yasunori Kindai Univ Grad Sch Sci & Engn 3-4-1 Kowakae Higashiosaka Osaka 5778502 Japan Kindai Univ Sch Sci & Engn 3-4-1 Kowakae Higashiosaka Osaka 5778502 Japan Univ Tsukuba Fac Engn Info & Syst 1-1-1 Tennodai Tsukuba Ibaraki 3058573 Japan

ISBN: (纸本)9781538626337

The Louvain method is one of the typical network clusterings. It is well-known that the Louvain method obtains better cluster partition in a short time. However, there are several network data which are not obtained better cluster partition by the Louvain method. One of the reasons for the above is that the Louvain method focuses on an only edge connection. We proposed the method which focuses on node size. The proposed method optimizes the objective function of k-medoids by solving the linear programming problem under the constraints on node size. We verified the usefulness of the proposed method in the viewpoint of calculation time and accuracy with an artificial and benchmark unweighted network datasets. The numerical examples show that the proposed method is faster and obtains better cluster partition than the Louvain method. The Euclidean distance in adjacency matrix does not obtain better cluster partition for the datasets, which consist of terminal nodes or high degree nodes.

关键词： network clustering linear programming problem modularity k-medoids controlled size

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On "Games with multiple payoffs"

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International Journal of Game Theory 1982年第1期11卷 13-15页

作者： Hannan, E.L. New York State Department of Health Office of Health Systems Management Albany 12237 New York Tower Building State Plaza United States

This note points out an error in a numerical example of a two-person, zero-sum game with vector payoffs provided by Zeleny [1975]. The resulting solution of the parametric linear programming problem is a mixed strateg... 详细信息

关键词： Economic Theory Game Theory programming problem linear programming problem Mixed Strategy

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A model of crop planning under uncertainty in agricultural management

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2003年 81-2卷 555-558页

作者： Itoh, T Ishii, H Nanseki, T Univ Marketing & Distribut Sci Fac Informat Sci Kobe Hyogo 6512188 Japan Osaka Univ Grad Sch Engn Suita Osaka 5650871 Japan Minist Agr Forestry & Fisheries Tsukuba Ibaraki 3058666 Japan

The crop planning problem is often formulated as a linear programming problem. But, in many actual cases, the profit coefficients for agricultural products are not certain values because of the influence of the future weather, so a linear programming model with constant coefficients does not describe the environment of decision making properly. Therefore, we propose a model of crop planning with uncertain (stochastic) values which may support decision making of agricultural farms. In this paper, we treat such uncertain elements as the values with the fuzziness and randomness. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： crop planning linear programming problem fuzzy constraint discrete random variable

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An iterative method, having linear rate of convergence, for solving a pair of dual linear programs

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Mathematical programming 1972年第1期3卷 302-311页

作者： Oettli, W. Rheinische Friedrich-Wilhelms-Universität Bonn Germany

关键词： Mathematical Method programming problem Iterative Method linear programming problem linear Rate

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Parabolic Intuitionistic Fuzzy based Data Envelopment Analysis

Parabolic Intuitionistic Fuzzy based Data Envelopment Analys...

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IEEE CIS International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Sahil, Mohammad Aqil Kaushal, Meenakshi Lohani, Q. M. Danish South Asian Univ Dept Math New Delhi 110021 India

ISBN: (纸本)9781665444071

A Fuzzy Data Envelopment Analysis (FDEA) is a popular technique to measure the relative efficiency of a Decision Making Unit (DMU) with respect to other DMUs under uncertain/imprecise information represented in form of fuzzy input and fuzzy output. However, in a real life application, due to higher order of uncertainty, the fuzzy set may not be a suitable choice, as the membership value alone cannot represent the input/output information precisely. Therefore in the paper, we extend the FDEA model to Intuitionistic Fuzzy Data Envelopment Analysis (IFDEA) model, namely, Parabolic Intuitionistic Fuzzy based Data Envelopment Analysis, where the input and output are demonstrated by Parabolic Intuitionistic Fuzzy Numbers (PIENs). Further the alpha-cut and beta-cut approach are used to convert the parabolic intuitionistic fuzzy inputs and outputs into their corresponding intervals and to compute the parametric efficiencies of the given DMUs. Additionally, we have used the section formula to defuzzify the parabolic intuitionistic fuzzy numbers into their crisp form to execute the optimization problem. Finally, the cross-efficiency technique is used to rank the DMUs.

关键词： linear programming problem Data Envelopment Analysis Cross-Efficiency Technique Intuitionistic Fuzzy Sets

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