Owing to the over-exploitation of fossil fuels, many governments have been promoting renewable energy to resolve the limitation of fossil energy and environmental problems. Nevertheless, most of the electricity data l...
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ISBN:
(纸本)9781479960651
Owing to the over-exploitation of fossil fuels, many governments have been promoting renewable energy to resolve the limitation of fossil energy and environmental problems. Nevertheless, most of the electricity data lack of systematic analysis to provide useful information. Furthermore, due to the development of cloud technology, these big data vary in type and time. Without appropriate big data analysis and user interface, data would provide error messages. Besides, few of the websites are built for enterprise to provide suggestion as a recommender. In summary, this study intends to develop a recommender system including cloud data base, analytical module and user interface. Based on continuous Markov chain, we analyze data according to the historical electricity data;through time series analysis and multi-objective programming models, a long-term investment of renewable energy decision supports and the best combination of renewable energy can be revealed. The research integrates these modules to construct an enterprise-oriented cloud system. To ensure the effectiveness of the platform, validation test will be performed. The result demonstrates that the recommender system can be used to assist the company in making the best investment of renewable energy and the best combination of energy consumption.
Randomness and fuzziness are two common uncertainties in decision process, and they always coexist in many real multi-objective problems such as resources allocation, complex system optimization. So it is a widespread...
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ISBN:
(纸本)9781467372206
Randomness and fuzziness are two common uncertainties in decision process, and they always coexist in many real multi-objective problems such as resources allocation, complex system optimization. So it is a widespread research content on the process problem of the two uncertainties in academic and application fields. In this paper, aimed at the multi-objective programming with fuzzy goals and random coefficients, we first propose the level effect function and construct the effect probability of fuzzy events by regarding the fuzzy goals as the fuzzy events. Then we discuss the probability of fuzzy number and the probability formulas of several special fuzzy events are further given. Besides, we establish the multi-objective programming maximum effect probability model (abbreviated as MOP-MEP model). Finally, we illustrate the validity of MOP-MEP model in combination with a case.
To achieve four goals of energy safety assurance, sustainable development, low-carbon environment and avoiding price volatility of fossil fuels, a new energy policy was announced by the government of Taiwan in Novembe...
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ISBN:
(纸本)9781479960651
To achieve four goals of energy safety assurance, sustainable development, low-carbon environment and avoiding price volatility of fossil fuels, a new energy policy was announced by the government of Taiwan in November 2011. Also, the Government will actively fulfill the carbon reduction target and electricity stable supply policy under three major principles of reaching international carbon reduction commitments, no limitation of electricity usage and valid electricity price. Consequently, the Government encourages private enterprises to generate electric power of renewable energy and sell back to the public enterprise. In order to support a private enterprise to evaluate the possible generation combination of the renewable energy under the consideration of intermittence of renewable energy, environmental protection and generation cost, given the monthly electricity demand, this study proposes 2-stage analytical model of which at the first stage, a multi-objective model is proposed to optimize the mix of the electricity from power company and the renewable energy generation in order to maximize the total energy generation of renewable energies, while minimizing carbon emission at a minimum cost;and at the second stage, a Markov chain model is developed to determine which combination of renewable energies is most likely to provide more power generations. By substituting the steady-state probability obtained from the second stage, the third goal of generation maximization under the stable power supply can be achieved.
In light of the rapid development of urbanization, this essay mainly studies the new type of metropolitan area during city evolution and researches about the rational allocation of intercity passenger transportation i...
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In this paper, we consider a fuzzy multi-choice linear programming problem where some of the parameters and decision variables are trapezoidal type fuzzy numbers. In order to defuzzify a general fuzzy quantity the con...
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In this paper, we consider a fuzzy multi-choice linear programming problem where some of the parameters and decision variables are trapezoidal type fuzzy numbers. In order to defuzzify a general fuzzy quantity the concept of nearest trapezoidal fuzzy number is introduced. By assuming all the decision variables as trapezoidal fuzzy number, the objective function and the left hand side of constraints are approximated to their nearest trapezoidal fuzzy number. Interpolating polynomials are formulated for all multi-choice type parameters. multi-choice type parameters are replaced by polynomials with integer variables. Then an equivalent multi-objective non linear programming problem is established. First and second objective functions represent left and right modal values of the trapezoidal type fuzzy number, where as the third and fourth objective functions represent the left and right spreads of the trapezoidal type fuzzy number. By applying lexicographic method optimal solution is obtained. In addition, a case study on a garment manufacture company is presented to demonstrate the solution procedure.
In many staff-assignment problems, a large variety of requirements has to be considered when assigning employees to work shifts. As the importance of the requirements is often described in a hierarchical manner, lexic...
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ISBN:
(纸本)9781467380676
In many staff-assignment problems, a large variety of requirements has to be considered when assigning employees to work shifts. As the importance of the requirements is often described in a hierarchical manner, lexicographic goal programming has been used to minimize the number of requirement violations. The resulting schedules are in general of high quality with respect to requirement violations but may lack acceptance by employees because of an unfair distribution of the violations. We introduce a novel approach for lexicographic goal programming that allows to improve an existing schedule in terms of fairness without deteriorating its quality with regard to requirement violations. The effectiveness of the proposed approach is demonstrated for a test set derived from real-world data.
In this paper, a revenue sharing contract is designed to coordinate a distribution channel where the demand of the product is ramp-type price and effort sensitive. It is shown that traditional revenue sharing contract...
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In this paper, a revenue sharing contract is designed to coordinate a distribution channel where the demand of the product is ramp-type price and effort sensitive. It is shown that traditional revenue sharing contract does not coordinate the system. As an alternative, two new mechanisms are proposed (i) revenue sharing with coordinated effort of the retailer alone and (ii) both revenue and effort sharing contract. In addition, a crucial modification of revenue sharing fraction is also proposed. To enhance the applicability of revenue sharing contract, the contract parameters are determined by using bi-level multi-objective fuzzy goal programming technique where manufacturer sets the wholesale price greater than the marginal cost. Numerical examples are presented to illustrate all the models.
The solution concept in multi-objective programming is represented by a program which reaches "the best compromise". Many solving methods find a good compromise feasible solution and then check whether the s...
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The solution concept in multi-objective programming is represented by a program which reaches "the best compromise". Many solving methods find a good compromise feasible solution and then check whether the solution is efficient or not. In this paper, using the efficiency test introduced by Lotfi et al. (2010) [12], we propose two procedures for deriving weakly and strongly efficient solutions in multi-objective linear fractional programming problems (MOLFPP) starting from any feasible solution, and present their possible applications in multiple criteria decision-making process. Then, we discuss a shortcoming of some fuzzy approaches to solving MOLFPP and modify them in order to guarantee the efficiency of the optimal solution. (C) 2013 Elsevier Inc. All rights reserved.
Municipal Solid Waste Management (MSWM) has become one of the main challenges of urban areas in the world. For developing countries, this situation is of greater severity due to disordered population growth, rapid ind...
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Municipal Solid Waste Management (MSWM) has become one of the main challenges of urban areas in the world. For developing countries, this situation is of greater severity due to disordered population growth, rapid industrialization, and deficiency in regulations, among other factors. One component of MSWM is the final disposal, where landfills are the most commonly used technologies for this purpose. According to a body of research, landfill location should meet the needs of all stakeholders, thus we propose a model based on multi-objective programming considering several decisions such as landfill opening, when they should be opened, and especially a common situation in our countries: the kind of expansion capacity that should be used. We present an example that reflects the conflict of two objectives: cost and environmental risk. The results show the allocation of each municipality to each landfill and the amount of municipal solid waste to be sent, among other variables.
A convergent product is an assembly shape concept integrating functions and sub-functions to form a final product. To conceptualize the convergent product problem, a web-based network is considered in which a collecti...
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A convergent product is an assembly shape concept integrating functions and sub-functions to form a final product. To conceptualize the convergent product problem, a web-based network is considered in which a collection of base functions and sub-functions configure the nodes, and each arc in the network is considered to be a link between two nodes. The aim is to find an optimal tree of functionalities in the network, adding value to the product in the web environment. First, an algorithm is proposed to assign the links among bases and sub-functions. Then, numerical values, as benefits and costs, are determined for arcs and nodes, respectively, using a mathematical approach. Also, customer value corresponding to the benefits is considered. Finally, the Steiner tree methodology is adapted to a multi-objective model optimized by an augmented epsilon-constraint method. An example is worked out to illustrate the proposed approach. (C) 2015 Sharif University of Technology. All rights reserved.
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