Optimization of the industry structure is important for the sustainable development for developing countries, e.g. China. The inexact stochastic multiple objectiveprogramming (ISMOP) which integrates stochastic progr...
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Optimization of the industry structure is important for the sustainable development for developing countries, e.g. China. The inexact stochastic multiple objectiveprogramming (ISMOP) which integrates stochastic programming, interval linear programming, and multiple objectiveprogramming was applied to analyze the optimization of industrial structure based on water environmental carrying capacity in Huai River Basin within Shandong Province (HRBSP). ISMOP can effectively solve the uncertainty existing in the multiple-objective optimization model and provide the information of development patterns of different industrial sectors. Results showed that the growth rates of output values from secondary industries under different q(i) values in the planning stage (2010-2020) will be almost 8%, and the total amounts of COD and NH3-N discharge will reduce by at least 65% from 2010 to 2020 in HRBSP. In term of the secondary industrial structure, the coal, paper-making and food processing industries, as the traditional backbone industries but with high risk of water pollution, should be reduced gradually;the beverage and textile industries should be strictly limited;and conversely, the new industries, such as metallurgy and construction material industries, should be allowed to maintain the rapid development. In the context of the aquatic environment protection in the basin level, the results based on ISMOP are useful for making policies to balance the economic development and water pollutant prevention within the Huai River Basin and other river basins. (C) 2015 Elsevier Ltd. All rights reserved.
Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply...
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Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry. (C) 2015 Elsevier Ltd. All rights reserved.
This note finds and resolves a compounding problem in the interactive multi-objective optimization method developed by Park and Shin (2012). The compounding problem means that the algorithm generates a solution unexpe...
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This note finds and resolves a compounding problem in the interactive multi-objective optimization method developed by Park and Shin (2012). The compounding problem means that the algorithm generates a solution unexpected by the decision maker. A concrete example of the compounding problem is demonstrated and, to remove the problem, an improved algorithm is then developed. We also show that the improved algorithm converges to the known optimal solutions faster than the earlier algorithm. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
Reverse logistics is believed to be one of the most promising solutions for capturing the remaining values from used products and has been extensively focused by both academics and practitioners during the past two de...
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Reverse logistics is believed to be one of the most promising solutions for capturing the remaining values from used products and has been extensively focused by both academics and practitioners during the past two decades. Conceptual framework, mathematical programming, and computational algorithms have been developed for decision-making at strategic, tactical, and operational levels of a reverse supply chain. In this paper, a novel idea for the design and planning of a general reverse logistics network is suggested and formulated through multi-objective mixed integer programming. The reverse logistics system is an independent network and comprises of three echelons for collection, remanufacturing, recycling, energy recovery, and disposal of used products. The mathematical model not only takes into account the minimization of system operating costs, but also considers minimization of carbon emissions related to the transportation and processing of used products, and the minimum rate of resource utilization is also required in order to minimize the waste of resources in landfill. Illustration, sensitivity analysis, and numerical experimentation are given to show the applicability and computational efficiency of the proposed model. This work provides an alternative approach to account both economic and environmental sustainability of a reverse logistics system. The result explicitly shows the trade-off between the costs and carbon emissions, cost effectiveness for improving environmental performance, and influences from resource utilization, all of which have great practical implication on decision-making of network configurations and transportation planning of a reverse logistics system. For future development of this work, suggestions are also given latter in this paper.
In course of the German power system transition to a higher share of renewable energy sources decentralized activities constitute a major driving force for the growth of renewable energy capacity. In this context plur...
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ISBN:
(纸本)9781509042371
In course of the German power system transition to a higher share of renewable energy sources decentralized activities constitute a major driving force for the growth of renewable energy capacity. In this context plural activities and initiatives on the local and regional level are followed to develop concepts for an efficient and sustainable regional energy supply. To achieve these goals various objectives has to be simultaneously accomplished. Generally, these objectives contradict to each other and cannot be handled by a single optimization technique. This paper proposes a multiobjective (MO) optimization approach for identifying efficient DG generation portfolios regarding multiple objectives. The methodology presented allows the planner to decide the best trade-off between the self-supply degree, environmental impact and electricity generation cost. The proposal applies, in a study case, a MO genetic algorithm that allows identifying a set of non-inferior Pareto-optimal solutions.
This paper proposes reasonable metric to measure the success of smart growth of a city and obtain the wise plan for cities. The whole work is carried out by means of comprehensive analysis under some hypothesized sett...
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This paper proposes reasonable metric to measure the success of smart growth of a city and obtain the wise plan for cities. The whole work is carried out by means of comprehensive analysis under some hypothesized settings. We set up five primary indicators: economic, society, environment, geographical conditions and demographics, each of which is subdivided into several secondary indicators. Analytic Hierarchy Process(AHP) Model is established to determine the weight of each indicator, which is adequately filled in the three-hierarchy structure. To overcome weakness of excess subjective factors in AHP, Fuzzy Synthetic Evaluation model is proposed to classify our indicators using data of 12 cities as samples. We divide scores into five levels in descending order: A, B, C, D and E. Combining the two models, the data is normalized, the eigenvalues and eigenvectors of judging matrix are calculated and the consistency test is conducted, which indicates robustness of our indicators classification.
A lot of attention has recently been paid to the crisis of the Kariba Dam on the Zambezi River. The dam is in urgent need of maintenance. In order to solve this problem, a series of models are established, and the con...
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A lot of attention has recently been paid to the crisis of the Kariba Dam on the Zambezi River. The dam is in urgent need of maintenance. In order to solve this problem, a series of models are established, and the construction scheme of the dams is studied in detail. At first we establish Safe Operation Model. In this model, we study the relationship between overflow risk rate and dam numbers to determine the approximate range of the quantity. We then analyze the cost and the benefits of the project. Finally, the number of dams is determined by the cost and the benefits. The optimal number of dams that we have calculated is 16. At last, we analyze the results of each of these models, performing sensitivity analysis on the input parameters and demonstrating their flexibility. Then we analyze the strength and weakness of the model.
Active distribution networks have the capability to allow the distributed energy resources integration at reasonable costs, opening new business opportunities. Although the sharing of responsibility among the system s...
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ISBN:
(纸本)9781424483570
Active distribution networks have the capability to allow the distributed energy resources integration at reasonable costs, opening new business opportunities. Although the sharing of responsibility among the system stakeholders (e.g., the Civil Society, the DSO and DER owners) is essential, undeniably they pursue different, and sometimes opposite goals. The authors, by adopting multiobjectiveprogramming to simulate the behavior of the stakeholders, aim at assessing how the system players will drive the distribution evolution under the influence of different regulatory environments. All the scenarios have been analyzed on a case study representative of a typical distribution system. The results presented can help Regulators to define a fairer asset and performance based distribution revenue.
Containership capacity allocation is an important issue since liner companies must avoid unused space on a voyage to maximize their revenue. Therefore, in the face of uncertain cargo demand and fiercely competitive ma...
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Containership capacity allocation is an important issue since liner companies must avoid unused space on a voyage to maximize their revenue. Therefore, in the face of uncertain cargo demand and fiercely competitive markets, liner carriers build revenue management systems to maximize voyage profits through careful consideration of slot allocation and pricing. A containership slot allocation model is proposed in this article to deal with two conflicting objectives: carrier's freight contribution and agents' degree of satisfaction, as well as fuzzy constraints, that is, uncertainties of cargo transportation demand and weight. This model is formulated using fuzzy multi-objective programming for deep-sea liner service containership slot allocation. Interactive fuzzy multi-objective linear programming with fuzzy parameters is applied to solve this problem. The proposed model is applied to an Asia-Europe service route of a liner company to test its efficacy. Results show the model's applicability and excellent performance in practice.
Wireless energy transfer capability and multi-tier network architecture are both envisioned as inherent features of the next generation wireless networks, on account of exponentially increasing low power connected dev...
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ISBN:
(纸本)9781509017010
Wireless energy transfer capability and multi-tier network architecture are both envisioned as inherent features of the next generation wireless networks, on account of exponentially increasing low power connected devices and the rising concern about their limited battery life. In this paper, we investigate joint resource allocation problem, for wireless information and energy transfer in small cells overlaid by macrocell. Using scalarization technique of multi-objective programming, we jointly optimize energy harvesting rate and achievable throughput of smallcell users while ensuring that minimum throughput requirement of macrocell user is satisfied. The formulated MINLP problem is converted to convex optimization problem by relaxing some variables and introducing auxiliary variables. We highlight the condition at which the obtained solution is the optimal solution of the original problem. Numerical results are presented to analyze the performance of the proposed resource allocation framework and show the improvement in achieved energy harvesting rate, by comparing with a benchmark scheme.
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