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Compromise Programming (compromise + programming)

Distribution by Scientific Domains

Engineering	75%

Selected Abstracts

INTEGRATING HUMANS IN ECOSYSTEM MANAGEMENT USING MULTI-CRITERIA DECISION MAKING,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2003
Georgios E. Pavlikakis
ABSTRACT: The Ecosystem Management (EM) process belongs to the category of Multi-Criteria Decision Making (MCDM) problems. It requires appropriate decision support systems (DSS) where "all interested people" would be involved in the decision making process. Environmental values critical to EM, such as the biological diversity, health, productivity and sustainability, have to be studied, and play an important role in modeling the ecosystem functions; human values and preferences also influence decision making. Public participation in decision and policy making is one of the elements that differentiate EM from the traditional methods of management. Here, a methodology is presented on how to quantify human preferences in EM decision making. The case study of the National Park of River Nestos Delta and Lakes Vistonida and Ismarida in Greece, presented as an application of this methodology, shows that the direct involvement of the public, the quantification of its preferences and the decision maker's attitude provide a strong tool to the EM decision making process. Public preferences have been given certain weights and three MCDM methods, namely, the Expected Utility Method, Compromise Programming and the Analytic Hierarchy Process, have been used to select alternative management solutions that lead to the best configuration of the ecosystem and are also socially acceptable. [source]

A Multiobjective and Stochastic System for Building Maintenance Management

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2000
Z. Lounis
Building maintenance management involves decision making under multiple objectives and uncertainty, in addition to budgetary constraints. This article presents the development of a multiobjective and stochastic optimization system for maintenance management of roofing systems that integrates stochastic condition-assessment and performance-prediction models with a multiobjective optimization approach. The maintenance optimization includes determination of the optimal allocation of funds and prioritization of roofs for maintenance, repair, and replacement that simultaneously satisfy the following conflicting objectives: (1) minimization of maintenance and repair costs, (2) maximization of network performance, and (3) minimization of risk of failure. A product model of the roof system is used to provide the data framework for collecting and processing data. Compromise programming is used to solve this multiobjective optimization problem and provides building managers an effective decision support system that identifies the optimal projects for repair and replacement while it achieves a satisfactory tradeoff between the conflicting objectives. [source]

Portfolio selection on the Madrid Exchange: a compromise programming model

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 1 2003
E. Ballestero
As a contribution to portfolio selection analysis, we develop a compromise programming approach to the investor's utility optimum on the Madrid Online Market. This approach derives from linkages between utility functions under incomplete information, Yu's compromise set, and certain biased sets of portfolios on the efficient frontier. These linkages rely on recent theorems in multi,criteria literature, which allow us to approximate the investor's utility optimum between bounds which are determined either by linear programming models or graphic techniques. Returns on 104 stocks are computed from capital gains and cash,flows, including dividends and rights offerings, over the period 1992,1997. The first step consists in normalizing the mean,variance efficient frontier, which is defined in terms of two indexes, profitability and safety. In the second step, interactive dialogues to elicit the investor's preferences for profitability and safety are described. In the third step, the utility optimum for each particular investor who pursues a buy,&,hold policy is bounded on the efficient frontier. From this step, a number of portfolios close to the investor's utility optimum are obtained. In the fourth step, compromise programming is used again to select one ,satisficing' portfolio from the set already bounded for each investor. This step is new with respect to previous papers in which compromise/utility models are employed. Computing processes are detailed in tables and figures which also display the numerical results. Extensions to active management policies are suggested. [source]

COMPROMISE PROGRAMMING METHODOLOGY FOR DETERMINING INSTREAM FLOW UNDER MULTIOBJECTIVE WATER ALLOCATION CRITERIA,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 5 2006
Jenq-Tzong Shiau
ABSTRACT: This paper presents a quantitative assessment framework for determining the instream flow under multiobjective water allocation criteria. The Range of Variability Approach (RVA) is employed to evaluate the hydrologic alterations caused by flow diversions, and the resulting degrees of alteration for the 32 Indicators of Hydrologic Alteration (IHAs) are integrated as an overall degree of hydrologic alteration. By including this index in the objective function, it is possible to optimize the water allocation scheme using compromise programming to minimize the hydrologic alteration and water supply shortages. The proposed methodology is applied to a case study of the Kaoping diversion weir in Taiwan. The results indicate that the current release of 9.5 m3/s as a minimum instream flow does not effectively mitigate the highly altered hydrologic regime. Increasing the instream flow would reduce the overall degree of hydrologic alteration; however, this is achieved at the cost of increasing the water supply shortages. The effects on the optimal instream flow of the weighting factors assigned to water supplies and natural flow variations are also investigated. With equal weighting assigned to the multiple objectives, the optimal instream flow of 26 m3/s leads to a less severely altered hydrologic regime, especially for those low-flow characteristics, thereby providing a better protection of the riverine environment. [source]