Dealing with the maritime transportation of crude oil and petroleum products has become a problem of major international concern due to the potential of environmental pollution created by oil spill incidents. This pap...
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Dealing with the maritime transportation of crude oil and petroleum products has become a problem of major international concern due to the potential of environmental pollution created by oil spill incidents. This paper presents the development of a strategic multiobjective network flow model, allowing for risk analysis and routing, with multiple commodities, modalities and origin-destination pairs. The development of an interactive solution methodology is also presented followed by its implementation via a World Wide Web-based software package. Government agencies will find the model helpful in determining how regulations should be set to derive desirable routing schemes. Shippers will also find the model useful in optimizing their logistics costs. (C) 2001 Elsevier Science Ltd. All rights reserved.
Dealing with the maritime transportation of crude oil and petroleum products has become a problem of major international concern due to the potential of environmental pollution created by oil spill incidents. This pap...
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Dealing with the maritime transportation of crude oil and petroleum products has become a problem of major international concern due to the potential of environmental pollution created by oil spill incidents. This paper presents the development of a strategic multiobjective network flow model, allowing for risk analysis and routing, with multiple commodities, modalities and origin-destination pairs. The development of an interactive solution methodology is also presented followed by its implementation via a World Wide Web-based software package. Government agencies will find the model helpful in determining how regulations should be set to derive desirable routing schemes. Shippers will also find the model useful in optimizing their logistics costs. (C) 2001 Elsevier Science Ltd. All rights reserved.
Designing water quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable submodels, competing objectives, unquantifiable factors, no...
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Designing water quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable submodels, competing objectives, unquantifiable factors, nonlinear characteristics, and uncertainty during parameterization. Mathematical optimization techniques offer promise in identifying optimal or satisfactory strategies that may be used as benchmarks for decision making. Newer optimization techniques such as genetic algorithm (GA) and fuzzy mathematical programming make the search for optimal control strategies in an uncertain environment more feasible. Using a probabilistic search procedure that emulates Darwinian natural selection, GAs allow multicriteria decision making with respect to both nonlinear feature and fuzzy characteristics to be incorporated directly into the optimization process and generate trade-off curves between cost and environmental quality while identifying good control strategies. This paper verifies such a discovery by a case study of water quality control in the Tseng-Wen river basin in Taiwan. (C) 1998 IAWQ. Published by Elsevier Science Ltd.
Designing water quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable submodels, competing objectives, unquantifiable factors, no...
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Designing water quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable submodels, competing objectives, unquantifiable factors, nonlinear characteristics, and uncertainty during parameterization. Mathematical optimization techniques offer promise in identifying optimal or satisfactory strategies that may be used as benchmarks for decision making. Newer optimization techniques such as genetic algorithm (GA) and fuzzy mathematical programming make the search for optimal control strategies in an uncertain environment more feasible. Using a probabilistic search procedure that emulates Darwinian natural selection, GAs allow multicriteria decision making with respect to both nonlinear feature and fuzzy characteristics to be incorporated directly into the optimization process and generate trade-off curves between cost and environmental quality while identifying good control strategies. This paper verifies such a discovery by a case study of water quality control in the Tseng-Wen river basin in Taiwan. (C) 1998 IAWQ. Published by Elsevier Science Ltd.
In this paper, a class of more general generalized convex functions: (F, p)-invariantconvexity functions, are defined. On the basis of defintions, we have constructed generalduality models (VD); discussed duality prop...
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In this paper, a class of more general generalized convex functions: (F, p)-invariantconvexity functions, are defined. On the basis of defintions, we have constructed generalduality models (VD); discussed duality property of (VP) and (VD); proved weakly dualitytheorem, direct duality theorem and converse duality theorem.
In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either possibilistic programming or multiobjective programming methods. Unfortunately, a...
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In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either possibilistic programming or multiobjective programming methods. Unfortunately, all these methods have shortcomings. In this note, using the concept of comparison of fuzzy numbers, we introduce a very effective method for solving these problems. Then we propose a new method for solving linear programming problems with fuzzy variables. (C) 2000 Elsevier Science B.V. All rights reserved.
The aim of the study is to develop a framework of applying life cycle assessment to production policy. A case-study on corrugated paperboard manufacture is therefore implemented. The application framework comprises th...
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The aim of the study is to develop a framework of applying life cycle assessment to production policy. A case-study on corrugated paperboard manufacture is therefore implemented. The application framework comprises three components: the conventional life cycle assessment procedure, the analytical hierarchy process, and a multiobjective programming model. In the decision model for production policy adjustment the objectives of cost-effectiveness and environment-friendliness are incorporated The environmental impacts are classified as categories of pollution and disturbance as well as space groups of global, regional and local scales. This makes applicable the analytical hierarchy process for evaluating the environmental impacts. In the application the objectives incorporated are found to be competitive. The manufacture has to trade the increase of production costs for the reduction of environmental impacts. We also observe that the marginal effects of impacts on cost increase as the spatial scales of impact increase. (C) 2000 Academic Press.
Utilities frequently use remote load control as an effective means to achieve suitable network operational conditions. This procedure, usually designated Load Management (LM), is a part of the resources considered und...
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Utilities frequently use remote load control as an effective means to achieve suitable network operational conditions. This procedure, usually designated Load Management (LM), is a part of the resources considered under the general designation of Demand-Side Management (DSM), However, the use of LM in electric distribution network management is a problem that involves different conflicting aspects such as reducing peak demand, maximizing utility profits and minimizing discomfort caused to consumers. Hence, the problem is multiobjective in nature: economical, technical and quality of service aspects must all be explicitly accounted for in mathematical models, This paper presents a multiobjective decision support model which allows the consideration of the main concerns that have an important role in LM: minimize peak demand as perceived by the distribution network dispatch center, maximize utility profit corresponding to the energy services delivered by the controlled loads, maximize quality of service in the context of LM.
This paper reviews multicriteria analysis applied to agricultural resource management. The applications utilize either methods for selecting multiattribute discrete alternatives (including multiattribute utility theor...
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This paper reviews multicriteria analysis applied to agricultural resource management. The applications utilize either methods for selecting multiattribute discrete alternatives (including multiattribute utility theory) or methods for solving multiobjective planning problems (including goal programming). Our main purpose is to classify and evaluate the criteria (attributes, objectives) used for modeling agricultural systems and to identify the difficulties for practitioners in applying the methodology. The fields of study in agricultural decisions requiring further investigation are also discussed. (C) 2000 Elsevier Science B.V. All rights reserved.
This paper develops a multiobjective programming model for the optimal allocation of passenger train services on an intercity high-speed rail line without branches. Minimizing the operator's total operating cost a...
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This paper develops a multiobjective programming model for the optimal allocation of passenger train services on an intercity high-speed rail line without branches. Minimizing the operator's total operating cost and minimizing the passenger's total travel time loss are the two planning objectives of the model. For a given many-to-many travel demand and a specified operating capacity, the model is solved by a fuzzy mathematical programming approach to determine the best-compromise train service plan, including the train stop-schedule plan, service frequency, and fleet size. An empirical study on the to-be-built high-speed rail system in Taiwan is conducted to demonstrate the effectiveness of the model. The case study shows that an optimal set of stop-schedules can always be generated for a given travel demand. To achieve the best planning outcome, the number and type of stop-schedules should be flexibly planned, and not constrained by specific stopping schemes as often set by the planner. (C) 2000 Elsevier Science Ltd. All rights reserved.
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