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possibilistic linear-programming FOR MANAGING INTEREST-RATE RISK

FUZZY SETS AND SYSTEMS 1993年第2期54卷 135-146页

作者： LAI, YJ HWANG, CL KANSAS STATE UNIV AGR & APPL SCI DEPT IND ENGNMANHATTANKS 66506

In this study, we consider the linear programming problem with the objective of the investment discounted value, where the interest rate is imprecise and has a triangular possibilistic distribution. An (crisp) auxiliary bi-objective linear programming model is proposed to resolve this possibilistic nature. Furthermore, we develop an extended Zimmermann approach, called augmented max-min approach, for solving this auxiliary bi-objective linear programming problem and other multiple objective linear programming problems. Finally, a numerical bank balance sheet problem, where interest rates, price of futures contract, loan demand, deposit supply and ratio of desired loan to deposit are assumed to be fuzzy, is solved for illustrating the new approach.

关键词： possibilistic linear programming INTEREST RATE RISK

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possibilistic linear programming Using General Necessity Measures Preserves the linearity

Possibilistic Linear Programming Using General Necessity Mea...

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8th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2011)

作者： Inuiguchi, Masahiro Osaka Univ Grad Sch Engn Sci Toyonaka Osaka 5608531 Japan

ISBN: (纸本)9783642225888

In this paper, a robust optimization approach to possibilistic linear programming problems is studied. After necessity measures and generation processes of logical connectives are reviewed, the necessity tractile optimization model of possibilistic linear programming problem is introduced as a robust optimization model. This problem is reduced to a linear semi-infinite programming problem. Assuming the convexity of the right parts of membership functions of fuzzy coefficients and the concavity of membership functions of fuzzy constraints, we investigate conditions on logical connectives for the problems to be reduced to linear programming problems. Several examples are given to demonstrate that necessity tractile optimization models are often reduced to linear programming problems.

关键词： possibilistic linear programming necessity measure implication function conjunction function

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A possibilistic linear programming model for supply chain network design under uncertainty

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IMA JOURNAL OF MANAGEMENT MATHEMATICS 2013年第2期24卷 209-229页

作者： Bouzembrak, Y. Allaoui, H. Goncalves, G. Bouchriha, H. Baklouti, M. Univ Lille Nord France F-59000 Lille France LGI2A UArtois F-62400 Bethune France Natl Sch Engineers Tunis Dept Ind Engn Tunis 1002 Tunisia

In this paper, we develop a possibilistic linear programming model for supply chain network design with imprecise inputs: market demands, supplied quantities, transportation costs, opening costs, treatment and storage costs are modelled as fuzzy numbers. An efficient possibilistic linear programme is constructed with fuzzy objective function that minimizes the sum of investment costs and operating costs of the supply chain. A method for solving the programming problem with fuzzy parameters is proposed. Application to a supply chain problem at a European textile company illustrates our methodology. Numerical results show that the performance of the proposed model in handling data uncertainty is better when compared to a classical deterministic model.

关键词： supply chain network design possibilistic linear programming fuzzy number uncertainty

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A NEW APPROACH TO SOME possibilistic linear-programming PROBLEMS

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FUZZY SETS AND SYSTEMS 1992年第2期49卷 121-133页

作者： LAI, YJ HWANG, CL KANSAS STATE UNIV AGR & APPL SCI DEPT IND ENGN MANHATTAN KS 66506 USA

In practice, the unit costs/profits of new products or new projects, the lending and borrowing interest rates, and cash flows are always imprecise. We provide an auxiliary multiple objective linear programming model to solve a linear programming problem with imprecise objective and/or constraint coefficients. Our strategy is to maximize the most possible value of the imprecise profit. At the same time, we would like to minimize the risk of obtaining lower profit and maximize the possibility of obtaining higher profit. This strategy is equivalent to the practical considerations of financial problems. In this paper, a numeric investment problem is solved for illustrating the new approach.

关键词： possibilistic linear programming MULTIPLE OBJECTIVE linear programming RISK

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Applying possibilistic linear programming to aggregate production planning

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2005年第3期98卷 328-341页

作者： Wang, RC Liang, TF Tung Nan Inst Technol Dept Ind Management Taipei 222 Taiwan Hsiuping Inst Technol Dept Ind Management Taichung 412 Taiwan

This work presents a novel interactive possibilistic linear programming (PLP) approach for solving the multi-product aggregate production planning (APP) problem with imprecise forecast demand, related operating costs, and capacity. The proposed approach attempts to minimize total costs with reference to inventory levels, labor levels, overtime, subcontracting and backordering levels, and labor, machine and warehouse capacity. The proposed approach uses the strategy of simultaneously minimizing the most possible value of the imprecise total costs, maximizing the possibility of obtaining lower total costs, and minimizing the risk of obtaining higher total costs. An industrial case demonstrates the feasibility of applying the proposed approach to real APP decision problems. Consequently, the proposed PLP approach yields an efficient APP compromise solution and overall degree of decision maker (DM) satisfaction with determined goal values. Particularly, several significant management implications and characteristics of the proposed PLP approach that distinguish it from the other APP decision models are presented. (c) 2004 Elsevier B.V. All rights reserved.

关键词： aggregate production planning possibilistic linear programming fuzzy sets theory

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Application of interactive possibilistic linear programming to aggregate production planning with multiple imprecise objectives

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PRODUCTION PLANNING & CONTROL 2007年第7期18卷 548-560页

作者： Liang, T.-F. Hsiuping Inst Technol Dept Ind Engn & Management Dali City 412 Taichung Taiwan

Aggregate production planning (APP) addresses matching supply to forecast demand, with varying customer orders over the intermediate planning horizon. In real-world APP problems, input data and related parameters are commonly imprecise because information is incomplete or unavailable, and the decision maker (DM) must simultaneously consider conflicting objectives. This study develops an interactive possibilistic linear programming (i-PLP) approach to solve multi-product and multi-time period APP problems with multiple imprecise objectives and cost coefficients by triangular possibility distributions in uncertain environments. The imprecise multi-objective APP model designed here seeks to minimise total production costs and changes in work-force level with reference to imprecise demand, cost coefficients, available resources and capacity. Additionally, the proposed i-PLP approach provides a systematic framework that helps the decision-making process to solve fuzzy multi-objective APP problems, enabling a DM to interactively modify the imprecise data and parameters until a set of satisfactory solutions is derived. An industrial case demonstrates the feasibility of applying the proposed approach to a practical multi-objective APP problem.

关键词： possibilistic linear programming aggregate production planning fuzzy set theory multi-objective linear programming

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MODELING OF CONSTRAINTS IN PROBLEMS OF possibilistic linear-programming

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JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL 1995年第4期33卷 71-75页

作者： YAZENIN, AV Tver' Univ

A system of linear constraints in the form of inequalities with possibilistic coefficients is investigated. A method is obtained for constructing a deterministic system of linear constraints that is equivalent to the ... 详细信息

关键词： possibilistic linear programming FUZZY VARIABLES EQUIVALENT DETERMINISTIC SYSTEM

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Demand and cost forecast error sensitivity analyses in aggregate production planning by possibilistic linear programming models

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JOURNAL OF INTELLIGENT MANUFACTURING 2000年第4期11卷 355-364页

作者： Hsieh, S Wu, MS Natl Taiwan Univ Dept Mech Engn Taipei 10764 Taiwan

A production management system contains many imprecise natures. The conventional deterministic and/or stochastic model in a computer integrated production management system (CIPMS) may not capture the imprecise natures well. This study examines how the imprecise natures in the CIPMS affect the planning results. possibilistic linear programming models are also proposed for the aggregate production planning problem with imprecise natures. The proposed model can adequately describe the imprecise natures in a production system and, in doing so, the CIPMS can adapt to a variety of non-crisp properties in an actual system. For comparison, the classic aggregate production planning problem given by Holt, Modigliani, and Simon (HMS) is solved using the proposed possibilistic model and the crisp model of Hanssmann and Hess (HH). Perturbing the cost coefficients and the demand allows one to simulate the imprecise natures of a real world and evaluate the effect of the imprecise natures to production plans by both the possibilistic and the crisp HH approaches. Experimental results indicate that the possibilistic model does provide better plans that can tolerate a higher spectrum of imprecise properties than those obtained by the crisp HH model.

关键词： possibilistic linear programming aggregate production planning computer integrated production management system imprecise properties sensitivity study

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Possibility distributions of fuzzy decision variables obtained from possibilistic linear programming problems

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FUZZY SETS AND SYSTEMS 2000年第2期113卷 323-332页

作者： Tanaka, H Guo, PJ Zimmermann, HJ Osaka Prefecture Univ Dept Ind Engn Sakai Osaka 593 Japan Rhein Westfal TH Aachen Lehrstuhl Unternehmensforsch D-52062 Aachen Germany

In this paper, several kinds of possibility distributions of fuzzy variables are studied in possibilistic linear programming problems to reflect the inherent fuzziness in fuzzy decision problems. Interval and triangular possibility distributions are used to express the non-interactive cases between the fuzzy decision variables, and exponential possibility distributions are used to represent the interrelated cases. possibilistic linear programming problems based on exponential possibility distributions become non-linear optimization problems. In order to solve optimization problems easily, algorithms for obtaining center vectors and distribution matrices in sequence are proposed. By the proposed algorithms, the possibility distribution of fuzzy decision variables can be obtained. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： interval variable triangular possibility distribution exponential possibility distribution fuzzy decision variable possibilistic linear programming

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RELATIVE MODALITIES AND THEIR USE IN possibilistic linear-programming

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FUZZY SETS AND SYSTEMS 1990年第3期35卷 303-323页

作者： INUIGUCHI, M ICHIHASHI, H Department of Industrial Engineering College of Engineering University of Osaka Prefecture 804 Mozu-Umemachi 4-cho Sakai Osaka 591 Japan

The relative modalities defined by possibility, necessity, impossibility and contingency of fuzzy sets in modal semantics are investigated. Decision procedures based on the modal concept are introduced and classified into eight classes. The relation between each decision procedure and the attitude of the decision maker toward uncertainty is discussed. Lastly, possibilistic linear programming relying on these decision procedures is formulated and a solution algorithm is proposed. A numerical example is given.

关键词： Possibility necessity relative possibility dual relative possibility possibilistic linear programming

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