This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy...
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This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy sources (supply basin (SB)), each of which is related to a biomass terminal. The objective of optimisation is based on both technical-logistics and environmental parameters. An SB is defined by the anisotropic weighted Voronoi tessellation methodology. The parameters are then aggregated to a multiobjective analysis that includes the optimisation of variables and compromise programming approach. Results permit the identification of the best supply chain organisation and the determination of the agroforest energy districts where rural policy and intervention could be applied. The model was tested in the province of Florence (central Italy) to depict efficient scenarios for the fuelling of DHPs.
Agricultural land use allocation involves assessment of land potential as well as land demand for various crops to identify the optimum land unit for each type. Current allocation models often focus on the perspective...
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Agricultural land use allocation involves assessment of land potential as well as land demand for various crops to identify the optimum land unit for each type. Current allocation models often focus on the perspective of increase in land demand. However, processes causing loss of arable land should be considered to correct the demand used in conventional allocation processes. In order to achieve that, a two stage model for crop allocation is presented which uses different models such as cellular automata, Markov chain, fuzzy rule-based system, goal programming and GIS raster analysis in a logical framework. In the presented model, at first by considering environmental (soil erosion and soil salinity) and economic (urban expansion) factors leading to arable land loss, agricultural use of each land unit is allocated. Next, crop types within the agricultural area are determined based on land suitability evaluation and demand assessment for each crop. This model is developed for rural land use planning on a regional scale and is applied to the Borkhar and Meymeh district in Isfahan province in Iran to predict land use map of 2015. The overall accuracy of 0.609 in the first step allowed us to draw conclusion that the inclusion of factors resulting farmland decline in allocation process gives more accurate results than the former allocation techniques which merely model factors causing increase in agricultural land areas. Moreover, according to the results for 2015, 27.82%, 21.64%, 7.27%, 5.85%, 7.36%, 6.36% and 1.74% of agricultural areas is allocated to wheat, wheat-maize, barley, barley-maize, maize, alfalfa and potato, respectively. The presented approach has advantageous to determine the crops with highest suitability for a given area according to the desired objectives. (C) 2014 Elsevier Ltd. All rights reserved.
For Intelligent Transportation Systems(ITS), dynamic traffic route choice is one of the most important technologies. Practical applications have shown that static route choice models can not meet passengers' trave...
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ISBN:
(纸本)9781479932795
For Intelligent Transportation Systems(ITS), dynamic traffic route choice is one of the most important technologies. Practical applications have shown that static route choice models can not meet passengers' travel demands, because route choice is a typical multi-objective programming problem affected by many dynamic factors, such as real-time traffic state, link travel time, traffic incident, intersection delay and so on. In this paper, I proposed a multi-objective dynamic route choice function with the minimum of link travel time and distance as the target, which travelers paid most attention to when they chose the route. Also I got travel time reliability as the model constraint to against the complexity and indetermination of traffic flow. And I obtained the link travel time by short-term forecasting based on measured traffic data of the network. Finally, in order to test its reliability, I established a simulation road network for real-time traffic data, and solved the model I put forward by improved genetic algorithm. Fortunately, I obtained an exciting result.
The third central moment and the capital budget are two important factors in designing the optimal hedge strategy. This paper investigates the problem of futures hedging under the third central moment and the capital ...
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The third central moment and the capital budget are two important factors in designing the optimal hedge strategy. This paper investigates the problem of futures hedging under the third central moment and the capital budget. Based on the multi-objective programming, a multi-objective hedging model with two important factors is proposed to manage this problem. Using the method of weighted sums, the multi-objective hedging model can be equivalently transformed into an ordinary single-objectiveprogramming. By solving the single-objectiveprogramming, we derive the optimal hedge ratio under the third central moment and the capital budget. Finally, an empirical example of hedging copper is given to illustrate the application of the proposed model. The results also show clearly the influence of the third central moment and the capital budget in the hedging decision. (C) 2013 Elsevier B.V. All rights reserved.
In this paper, we have studied the overtaking process on the two-way four-lane highway in China by using the theory of multi-objective programming, establish a traffic volume model and evaluate the safety of overtakin...
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ISBN:
(纸本)9783038351153
In this paper, we have studied the overtaking process on the two-way four-lane highway in China by using the theory of multi-objective programming, establish a traffic volume model and evaluate the safety of overtaking. In order to working out the optimal offset angle, we also establish the function equation between safety coefficient, traffic flow and the offset angle during overtaking or lane-changes. Finally some safer and smarter overtaking rules are put forward by combining the offset angle and the security constraints, thus improving the safety, intelligence and traffic flow.
Strategic network planning activities of national and even more of multinational companies are recently influenced by an increasing number of laws and regulations regarding environmental issues. On top of that non-gov...
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This paper seeks to investigate methodology on the seamless integration for constructing a climate-conscious building envelope. The focus is targeted to provide architectural designers with an intelligent way to devel...
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Integrated risk control and asset optimization is an important issue in commercial bank industry. This paper combines balance sheet with income statement, and forms a structure measuring each asset's risk based on...
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Integrated risk control and asset optimization is an important issue in commercial bank industry. This paper combines balance sheet with income statement, and forms a structure measuring each asset's risk based on the method using income statement only, having a better use of the data resource. Considering the commercial bank's diversified pursuit of low risk and high profit, we solve the problem using the method of multiple objectiveprogramming, and we give the Pareto surface to support selection decisions. The analysis framework of the integrated risk optimization based on financial statements provides a feasible idea for commercial banks' asset optimization research with limited data resource. (C) 2014 The Authors. Published by Elsevier B.V. Open access under CC BY-NC-ND license.
The inventory control model based on the multi-objective programming of the spare parts is set up. The algorithm of particle swarm optimization (PSO) is designed and improved to solve the inventory control multi-objec...
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ISBN:
(纸本)9781479952458
The inventory control model based on the multi-objective programming of the spare parts is set up. The algorithm of particle swarm optimization (PSO) is designed and improved to solve the inventory control multi-objective programming model. Aiming at the question of the particle that deviates from the solution space and the prematurity problem in the searching course, the regain mechanism and interference mechanism are built up to improve the classical PSO, and the switching mechanism from the Cartesian space to the discrete space of inventory control model is established, and then the optimized solution algorithm based on the improved PSO is presented. At last, the simulation experiments of inventory control are made to validate the multi-objective programming model. It lays the foundation for design and realization of simulation and optimization of inventory control of the spare parts.
The mitigation of adverse effects of agriculture on ecosystems, due to the use of agrochemicals and irrigation water, is expected to have implications on farm incomes. This study examines the possibilities of simultan...
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