In the background of regional emergency resource guarantee engineering to respond to earthquake disasters, a multi-objective model of cost-efficiency equilibrium problem is built to guarantee the supply of single emer...
详细信息
In the background of regional emergency resource guarantee engineering to respond to earthquake disasters, a multi-objective model of cost-efficiency equilibrium problem is built to guarantee the supply of single emergency resource in an area, combined with qualitative analysis of key factors affecting the resource layout. The model quantifies constitutional indexes about emergency resource guarantee cost and rescue efficiency. With robust optimization ideas, the model is transformed to single-objectiveprogramming model according to three decision criteria, and solved with branch-and-bound algorithm by Lingo software. Finally, a numerical example is illustrated to verify the model and decision criteria.
Aiming at the problem of resource allocation, this paper establishes a regional water resource allocation model based on a multi-objective programming algorithm. Specifically, we establish a linear programming model t...
详细信息
Aiming at the problem of resource allocation, this paper establishes a regional water resource allocation model based on a multi-objective programming algorithm. Specifically, we establish a linear programming model to identify two reservoirs with optimal water supply quantity and optimal power generation volume as objective functions. In addition, we establish a multi-objective programming model and determined the functional expressions of the two objectives of social benefit and economic benefit. The entropy weight method is used to determine the weights of the four major indicators of industry, agriculture, housing and electricity. Finally, we use MATLAB to solve the corresponding water demand, and use SPSS software to analyze the correlation between water, electricity supply and water demand, and obtain the influence of different variables in the model.
In most multi-objective optimization problems we aim at selecting the most preferred among the generated Pareto optimal solutions (a subjective selection among objectively determined solutions). In this paper we consi...
详细信息
In most multi-objective optimization problems we aim at selecting the most preferred among the generated Pareto optimal solutions (a subjective selection among objectively determined solutions). In this paper we consider the robustness of the selected Pareto optimal solution in relation to perturbations within weights of the objective functions. For this task we design an integrated approach that can be used in multi-objective discrete and continuous problems using a combination of Monte Carlo simulation and optimization. In the proposed method we introduce measures of robustness for Pareto optimal solutions. In this way we can compare them according to their robustness, introducing one more characteristic for the Pareto optimal solution quality. In addition, especially in multi-objective discrete problems, we can detect the most robust Pareto optimal solution among neighboring ones. A computational experiment is designed in order to illustrate the method and its advantages. It is noteworthy that the Augmented Weighted Tchebycheff proved to be much more reliable than the conventional weighted sum method in discrete problems, due to the existence of unsupported Pareto optimal solutions. (C) 2014 Elsevier B.V. All rights reserved.
Fuzzy rough bi-level multi-objective nonlinear programming problem (FRBMNPP) moved toward becoming rise normally in various real applications. In this article we develop bi-level multi-objective nonlinear programming ...
详细信息
Fuzzy rough bi-level multi-objective nonlinear programming problem (FRBMNPP) moved toward becoming rise normally in various real applications. In this article we develop bi-level multi-objective nonlinear programming problem (BMNPP), in which the objective functions have fuzzy nature and the constraints represented as a rough set. The fuzzy objective functions converted into deterministic ones by utilizing the alpha-cut methodology. Thus the FRBMNPP become a rough BMNPP which is transformed into two problems corresponding to the upper and lower approximation models. The Karush-Kuhn-Tucker (KKT) method and two models of technique of order preferences by similarity to ideal solution (TOPSIS) approach are developed to solve such problem. At last, applicability and efficiency of the two TOPSIS models and KKT method, suggested in this study, are presented through an algorithm and a numerical illustration. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.
The expected rate of earnings and risk of high-tech projects are very fuzzy, and investors hope to get the expected rate of earnings maximization and risk minimization. Therefore, this paper establishes the model of f...
详细信息
The expected rate of earnings and risk of high-tech projects are very fuzzy, and investors hope to get the expected rate of earnings maximization and risk minimization. Therefore, this paper establishes the model of fuzzy multi-objective programming method to select an optimal portfolio scheme. On the one hand, the objectives risk can be scattered, on the other hand investors can get ideal earnings. The example shows that this method to solve problems of portfolio investment decision is feasible and effective.
This paper developed a multi-objective fuzzy programming method for simultaneously optimizing the use of water and land resources for irrigation under uncertainty. The developed model was then applied to a case study ...
详细信息
This paper developed a multi-objective fuzzy programming method for simultaneously optimizing the use of water and land resources for irrigation under uncertainty. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, administrative, economic and ecological benefits were regarded as the planning objectives. Moreover, the variations of irrigation water demand with rainfall, soil moisture content and evapotranspiration were considered in the developed model. Optimal irrigation plans were obtained under different possibility levels of fUzzy parameters. The obtained results could be helpful for decision makers to make decisions on the optimal use of irrigation water and land resources under uncertainty and multiple objectives. (C) 2017 Elsevier Ltd. All rights reserved.
The problem of solving multi-objective linear-programming problems, by assuming that the decision maker has fuzzy goals for each of the objective functions, is addressed. Several methods have been proposed in the lite...
详细信息
The problem of solving multi-objective linear-programming problems, by assuming that the decision maker has fuzzy goals for each of the objective functions, is addressed. Several methods have been proposed in the literature in order to obtain fuzzy-efficient solutions to fuzzy multi-objective programming problems. In this paper we show that, in the case that one of our goals is fully achieved, a fuzzy-efficient solution may not be Pareto-optimal and therefore we propose a general procedure to obtain a non-dominated solution, which is also fuzzy-efficient. Two numerical examples illustrate our procedure. (C) 2008 Elsevier B.V. All rights reserved.
In the last 10 years much has been written about the drawbacks of radial projection. During this time, many authors proposed methods to explore, interactively or not, the efficient frontier via non-radial projections....
详细信息
In the last 10 years much has been written about the drawbacks of radial projection. During this time, many authors proposed methods to explore, interactively or not, the efficient frontier via non-radial projections. This paper compares three families of data envelopment analysis (DEA) models: the traditional radial, the preference structure and the multi-objective models. We use the efficiency analysis of Rio de Janeiro Odontological Public Health System as a background for comparing the three methods through a real case with one integer and one exogenous variable. The objectives of the study case are ( i) to compare the applicability of the three approaches for efficiency analysis with exogenous and integer variables, (ii) to present the main advantages and drawbacks for each approach, (iii) to prove the impossibility to project in some regions and its implications, (iv) to present the approximate CPU time for the models, when this time is not negligible. We find that the multi-objective approach, although mathematically equivalent to its preference structure peer, allows projections that are not present in the latter. Furthermore, we find that, for our case study, the traditional radial projection model provides useless targets, as expected. Furthermore, for some parts of the frontier, none of the models provide suitable targets. Other interesting result is that the CPU-time for the multi-objective formulation, although its endogenous high complexity, is acceptable for DEA applications, due to its compact nature.
In financial investment, risk and benefit coexist. How to balance the benefits and risks and find the optimal investment portfolio is a key issue to be considered by investors. In this research, BP neural network is u...
详细信息
In financial investment, risk and benefit coexist. How to balance the benefits and risks and find the optimal investment portfolio is a key issue to be considered by investors. In this research, BP neural network is used to predict the future return on equity(ROE) of asset;a multiobjectiveprogramming model of investment portfolio is established on the basis of Markowitz's portfolio investment theory;to select the optimal investment portfolio, a comparison is made on the benefit-risk ratio of the investment portfolio with the smallest risk and at different income levels;in addition, an empirical analysis is made on the basis of the quarterly ROE data of 5 stocks during 2002-2017.
In this paper, new classes of generalized convex functions are introduced for non-smooth multi-objective programming problem, mixed type dual problem is established, weak, strong duality theorems are derived under new...
详细信息
ISBN:
(纸本)9781509048410
In this paper, new classes of generalized convex functions are introduced for non-smooth multi-objective programming problem, mixed type dual problem is established, weak, strong duality theorems are derived under new convexity.
暂无评论