In this study a general methodology employing fuzzy analytic hierarchy process and fuzzy goal programming is developed for selection problems. The proposed methodology has two main sub-phases. In the first phase, fuzz...
详细信息
In this study a general methodology employing fuzzy analytic hierarchy process and fuzzy goal programming is developed for selection problems. The proposed methodology has two main sub-phases. In the first phase, fuzzy triangular numbers are used in order to represent the comparisons among decision criteria. Then lower and upper bounds as well as mid-values of priorities belonging to each decision criteria are computed. In the second phase these values and fuzzy triangular numbers are entered into the goal programming model and the model is solved to give the final priorities of decision criteria. Then the weighted sum of ratings for each selection alternative are found where the weights are final priorities from goal programming model. The proposed methodology is presented on a real life roadheader selection problem from mining industry. The results revealed that the methodology is easily applicable and provides satisfactory results.
The coordinate operating process of a supply chain is considered. The supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of th...
详细信息
The coordinate operating process of a supply chain is considered. The supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of the manufacturer, demands of customers are uncertain, and the uncertainties of demands are described as fuzzy sets. A multi-objective fuzzy programming model for coordinate operations of the supply chain is constructed and a numerical example is proposed. The results of the numerical example shows that decision makers can obtain an optimal operations strategy by using the model proposed in this paper according to the level of uncertainties of demands, and the operation strategy possesses robustness in same ways.
Networks are a powerful and useful tool for analysing complex systems. Three main types of networks have been proposed in the relative literature in order to interpret adequately evolving or stationary phenomena. In t...
详细信息
Networks are a powerful and useful tool for analysing complex systems. Three main types of networks have been proposed in the relative literature in order to interpret adequately evolving or stationary phenomena. In this research, two network structures are analysed;the first type is the random network, which was initially introduced by Erdos and Renyi. Random networks properties remain the same over time, and they do not exhibit high degree of clustering, whereas the second structure studied, the power-law network that have been examined by Albert and Barabasi, can incorporate attributes that are observed in natural networks (i.e. the World Wide Web and the authors' collaboration). In this study, an attempt is made to investigate the conditions under which random network and power law (or scale free) converge into one at a given time point. Three main metrics are used in order to examine the proximity between the studied structures: (i) clustering coefficient, (ii) average path length and (iii) degree distribution. Considering the difference of the corresponding metrics of each network type as an objective function, a multi-objective discontinuous non-linear programming model is employed using the weighted sum model as a solution approach. A statistical meta-analysis is performed using a multivariate logit model in order to assess the effect of each network's specific variables on the objective function. Copyright (C) 2015 John Wiley & Sons, Ltd.
In this paper, an algorithm is developed to solve a multi-objective Integer Indefinite Quadratic programming Problem(IQMPP). The cutting plane technique finds all the non-dominated p-tuples of the (IQMPP) problem. Sin...
详细信息
In this paper, an algorithm is developed to solve a multi-objective Integer Indefinite Quadratic programming Problem(IQMPP). The cutting plane technique finds all the non-dominated p-tuples of the (IQMPP) problem. Since the objective functions of (IQMPP) problem are quasi-monotone, the cutting plane truncates a portion of the feasible region and enables us to find all the non-dominated p-tuples at extreme points of the remaining feasible region. The algorithm is explained with the help of an example.
In the present paper, a new Gamma cost function is proposed for an optimum allocation in multivariate stratified random sampling with linear regression estimator. Extended lexicographic goal programming is used for so...
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 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 proposes a multi-objective preventative-emergency coordinated control (MO-PECC) method for high wind-penetrated power systems. The method facilitates utility-grade energy storage (ES) to realize post-contin...
详细信息
ISBN:
(纸本)9781538642924
This paper proposes a multi-objective preventative-emergency coordinated control (MO-PECC) method for high wind-penetrated power systems. The method facilitates utility-grade energy storage (ES) to realize post-contingency emergency control, and can generate indicator of system instability risk for solution sets. Once an unstable post-contingency system is detected, the ES systems immediately react for power injection/retraction, thus achieving emergency control to alleviate short-term system power imbalance and stabilizing the system together with synchronous generators. Numerical tests are performed on a modified IEEE-39 system, in which 3 synchronous generators are replaced by 3 same-scale wind farms. The test results verified the effectiveness of the proposed coordinated method, and the calculating time is relatively small, which is suitable for online calculation.
Mobile satellite communication systems play an important role in space information networks. They mostly operate at the L or S band and have multiple beams efficiently reusing the limited spectrum. Advanced technologi...
详细信息
Mobile satellite communication systems play an important role in space information networks. They mostly operate at the L or S band and have multiple beams efficiently reusing the limited spectrum. Advanced technologies, such as beamforming, are used to generate numerous beams through multiple feeders, and each beam's power allocation is correlated and constrained. Frequency reuse among multiple beams results in co-channel interference issue, which makes bandwidth allocation among multiple beams coupled. It is a challenging topic to optimize the resource allocation in the real-time service traffic. In this article, a new multi-objective programming scheme is used to solve the dynamic resource allocation problem, guaranteeing high quality-of-service for multiple services of different priorities. Since the dynamic resource allocation problem is formulated as NP-hard, a new traffic-aware dynamic resource allocation (TADRA) algorithm is proposed. This algorithm is proved to be optimal in terms of the Pareto-front under constraints of co-channel interference and onboard transmit power. Simulation results show that the trade-off is well balanced between the call completion ratio in high priority and the throughput for video and data services in medium and low priorities. Additionally, it is shown that the new multi-objective programming scheme, based on the traffic-awareness dynamic resource allocation algorithm, can rapidly achieve the Pareto-front solutions and reduce the computing complexity to a large extent.
The forecast of the scale of highway network is of great importance in the planning of regional highway network. This paper is to seek a hybrid method to improve the accuracy and reliability of scale-forecast and obta...
详细信息
The forecast of the scale of highway network is of great importance in the planning of regional highway network. This paper is to seek a hybrid method to improve the accuracy and reliability of scale-forecast and obtain the optimal hierarchical structure of highway network in Hangzhou in the Year 2015, 2020 and 2025. Firstly, drawbacks of traditional scale-forecast methods of highway network and advantages of the combinative forecast method which embraces BP neural network (BPNN) and Markov chain are illustrated. Then, a novel prediction method which is based on BPNN and Markov chain with the consideration of five elements, including GDP, total population, the number of civil motor vehicle ownership, passenger capacity and volume of freight traffic is proposed. After that, a multi-objective programming (MOP) model is established to obtain the optimum technical grade structure of highway network. Thirdly, with the Program for the 13th Five-Year Development Plan of Highway Transportation in Hangzhou, the scale of highway and its optimal hierarchical structure in the year of 2015, 2020 and 2025 is obtained. Finally, the results show that the accuracy and reliability of the forecast method are improved, and the model proves to be of both theoretical and practical significance.
暂无评论