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.
Electric vehicles have multiple action in energy conservation, load shifting, etc. Proper charging facilities planning methods and models can guide construction, and promote the development of electric vehicles. Based...
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Electric vehicles have multiple action in energy conservation, load shifting, etc. Proper charging facilities planning methods and models can guide construction, and promote the development of electric vehicles. Based on the regional characteristics of urban road network, this paper proposes a multiobjectiveprogramming model to configure electric vehicle charging station for urban road network. In this model, our objective is to maximize the total captured traffic, and to minimize the distribution network loss and voltage offset. Our model takes into account not only the convenience of the users, but also the impact on power quality and system operation and economy after charging stations are accessed to distribution systems. Using super-efficiency DEA model, we determine the objective function weights. And thus, the multiobjectiveprogramming is converted to a single-objectiveprogramming problems. And then improve BPSO algorithm is used to solve this single-objective optimization problem after conversion.
Two key decisions in designing cellular manufacturing systems are cell formation and layout design problems. In the cell formation problem, machine groups and part families are determined while in the facility layout ...
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Two key decisions in designing cellular manufacturing systems are cell formation and layout design problems. In the cell formation problem, machine groups and part families are determined while in the facility layout problem the location of each machine in each cell (intra-cell layout) and the location of each cell (inter-cell layout) are decided. Owing to the fact that there are interactions between two problems, cell formation and layout design problem must be tackled concurrently to design a productive manufacturing system. In this research, two problems are investigated concurrently. Some important and realistic factors such as inter-cell layout, intra-cell layout, operations sequence, part demands, batch size, number of cells, cell size, and variable process routings are incorporated in the problem. The problem is formulated as a mathematical model. Three different methods are described to solve the problem: multi-objective scatter search (MOSS), non-dominated genetic algorithm (NSGA-II), and the epsilon-constraint method. The methods are employed to solve nine problems generated and adopted from the literature. Sensitivity analysis is accomplished on the parameters of the problem to investigate the effects of them on objective function values. The results show that the proposed MOSS algorithm performs better than NSGA-II and produces better solutions in comparison to multi-stage approaches.
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