This article proposes a multi-currency cross-hedging strategy that minimizes the exchange risk. The use of derivatives in small and medium-sized enterprises (SMEs) is not common but, despite its complexity, can be int...
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This article proposes a multi-currency cross-hedging strategy that minimizes the exchange risk. The use of derivatives in small and medium-sized enterprises (SMEs) is not common but, despite its complexity, can be interesting for those with international activities. In particular, the reduction in the exchange risk borne through the use of natural multi-currency cross-hedging is measured, considering Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) for measuring market risk instead of the variance. CVaR is minimized using linear programmes, while a multiobjective genetic algorithm is designed for minimizing VaR, considering two scenarios for each currency. The results obtained show that the optimal hedge strategy that minimizes VaR is different from the minimum CVaR hedge strategy. A very interesting point is that, just by investing in other currencies, a significant risk reduction in VaR and CVaR can be obtained. (c) 2015 AEDEM. Published by Elsevier Espana, S.L.U.
Airline crew pairing problems involve optimizing an overall evaluation function containing various conflicting objectives and constraints originating from cost and safety considerations. Classical approaches based on ...
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Airline crew pairing problems involve optimizing an overall evaluation function containing various conflicting objectives and constraints originating from cost and safety considerations. Classical approaches based on set partitioning or set covering methods separate the solution into two phases, pairing generation and pairing optimization, and evaluate the cost by a weighted-sum of objective values. This paper proposes a new multiobjective evolutionary approach to improve the classical solution flow by integrating the two-phase steps as a single step and reasoning the multiple practical objectives simultaneously. Furthermore, this paper also examines real-life daily pairing problems in a Taiwanese short-haul airline as case studies. Compared to man-made pairing plans, the positive experimental results demonstrate the more appropriate and effective crew pairing plans explored according to practical considerations. These considerations include objectives such as duty connection, transition time, layover, pairing number, aircraft changing limes, flying time, and duty period.
Recently, the problem of clustering categorical data, where no natural ordering among the elements of a categorical attribute domain can be found, has been gaining significant attention from researchers. With the grow...
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Recently, the problem of clustering categorical data, where no natural ordering among the elements of a categorical attribute domain can be found, has been gaining significant attention from researchers. With the growing demand for categorical data clustering, a few clustering algorithms with focus on categorical data have recently been developed. However, most of these methods attempt to optimize a single measure of the clustering goodness. Often, such a single measure may not be appropriate for different kinds of datasets. Thus, consideration of multiple, often conflicting, objectives appears to be natural for this problem. Although we have previously addressed the problem of multiobjective fuzzy clustering for continuous data, these algorithms cannot be applied for categorical data where the cluster means are not defined. Motivated by this, in this paper a multiobjective genetic algorithm-based approach for fuzzy clustering of categorical data is proposed that encodes the cluster modes and simultaneously optimizes fuzzy compactness and fuzzy separation of the clusters. Moreover, a novel method for obtaining the final clustering solution from the set of resultant Pareto-optimal solutions in proposed. This is based on majority voting among Pareto front solutions followed by k-nn classification. The performance of the proposed fuzzy categorical data-clustering techniques has been compared with that of some other widely used algorithms, both quantitatively and qualitatively. For this purpose, various synthetic and real-life categorical datasets have been considered. Also, a statistical significance test has been conducted to establish the significant superiority of the proposed multiobjective approach.
This work presents a real time testing approach of an Intelligent multiobjective Nonlinear-Model Predictive Control Strategy (iMO-NMPC). The goal is the testing and analysis of the feasibility and reliability of some ...
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This work presents a real time testing approach of an Intelligent multiobjective Nonlinear-Model Predictive Control Strategy (iMO-NMPC). The goal is the testing and analysis of the feasibility and reliability of some Soft Computing (SC) techniques running on a real time industrial controller. In this predictive control strategy, a multiobjective genetic algorithm is used together with a Recurrent Artificial Neural Network in order to obtain the control action at each sampling time. The entire development process, from the numeric simulation of the control scheme to its implementation and testing on a PC-based industrial controller, is also presented in this paper. The computational time requirements are discussed as well. The obtained results show that the SC techniques can be considered also to tackle highly nonlinear and coupled complex control problems in real time, thus optimising and enhancing the response of the control loop. Therefore this work is a contribution to spread the SC techniques in on-line control applications, where currently they are relegated mainly to be used off-line, as is the case of optimal tuning of control strategies. (C) 2014 Elsevier B.V. All rights reserved.
This letter presents a high efficiency short backfire antenna (SBFA) using electromagnetically hard walls. A hard surface composed of low permittivity dielectric liner with longitudinal metal surface strips is affixed...
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This letter presents a high efficiency short backfire antenna (SBFA) using electromagnetically hard walls. A hard surface composed of low permittivity dielectric liner with longitudinal metal surface strips is affixed to the inside walls of a conventional SBFA's main reflector. The hard-walled SBFA was optimized to operate at L1 and L2 GPS bands with circular polarization using an R2 indicator based evolutionary multiobjectivealgorithm. A hard-walled SBFA with 2 lambda aperture diameter at L1 achieved 90% and 98% aperture efficiency at L1 and L2, respectively. Also the antenna exhibited more than 90% aperture efficiency over 16% bandwidth around L1. Compared to a conventional SBFA with the same aperture diameter the new antenna achieves 1.25 dB higher directivity at L1 and 0.76 dB at L2, as well as improved cross-polarization due to a more uniform aperture distribution.
Relevance feedback has been adopted as a standard in Content Based Image Retrieval (CBIR). One major difficulty that algorithms have to face is to achieve and adequate balance between the exploitation of already known...
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Relevance feedback has been adopted as a standard in Content Based Image Retrieval (CBIR). One major difficulty that algorithms have to face is to achieve and adequate balance between the exploitation of already known areas of interest and the exploration of the feature space to find other relevant areas. In this paper, we evaluate different ways to combine two existing relevance feedback methods that place unequal emphasis on exploration and exploitation, in the context of distance based methods. The hybrid approach proposed has been evaluated by using three image databases of various sizes that use different descriptors. Results show that the hybrid technique performs better than any of the original methods, highlighting the benefits of combining exploitation and exploration in relevance feedback tasks. (C) 2015 Elsevier B.V. All rights reserved.
Variable-length codes are classically used for source coding to compress data. However, Variable-Length Error-Correcting (VLEC) codes can also be used for channel coding where they are able to overcome the effects of ...
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ISBN:
(纸本)9781509000593
Variable-length codes are classically used for source coding to compress data. However, Variable-Length Error-Correcting (VLEC) codes can also be used for channel coding where they are able to overcome the effects of channel impairments by detecting and correcting bit errors. Multi-objective optimization is an area of multiple criteria decision making, where an optimization algorithm attempts to solve a problem with more than one objective. In this paper, VLEC codes are constructed by taking into consideration their two main properties: Average Codeword Length and Free Distance, associated respectively with their source and channel coding aspects. These two properties are taken as objectives in a Multi-objective global optimization geneticalgorithm. It is shown that better codes can be constructed using this algorithm.
Present study deals with the development of hydraulic and thermal design model of chevron type plate evaporator and optimization of its geometrical parameters for a low temperature geothermal ORC system. The optimizat...
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Present study deals with the development of hydraulic and thermal design model of chevron type plate evaporator and optimization of its geometrical parameters for a low temperature geothermal ORC system. The optimization is performed using Non-dominated Sorting geneticalgorithm-II (NSGA-II). The primary geometrical parameters of evaporator are selected as decision variables which include length, width and plate spacing. The minimum cost of evaporator and minimum pressure drop are chosen as objective functions under restriction of constant amount of heat transfer. Since the objective functions are conflicting, a single value of decision variables cannot satisfy both objective functions simultaneously. Therefore optimization results are presented in the form of Pareto Front solution which is trade-off between pressure drop and cost of evaporator. The minimum cost evaporator is 1570$ corresponding to pressure drop of 125 kPa while the maximum cost is 6988$ corresponding to a pressure drop of 5.2 kPa. The sensitivity analysis shows that the plate length has promising effect on pressure drop and cost of evaporator. Furthermore, the effect of pressure drop on cost of evaporator and net power of ORC system is also investigated. The optimum value of allowable pressure drop is 30-40 kPa, corresponding to net power of 73-74 kW of ORC system and cost of evaporator 3000-3500$. (C) 2015 Elsevier Ltd. All rights reserved.
In order to establish new healthcare facilities, their optimal number and locations should be determined. Unsuitable locations for these facilities may result in substandard customer services and increased expenses. T...
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In order to establish new healthcare facilities, their optimal number and locations should be determined. Unsuitable locations for these facilities may result in substandard customer services and increased expenses. To solve this location-allocation problem, this study applied a multiobjective model that combined geographical information system (GIS) analysis with amultiobjective genetic algorithm. Optimum sites for new clinics were determined by considering four objectives: minimizing total travel cost, minimizing inequity in access to clinics, minimizing the land-use incompatibility in the study area, and minimizing the costs of land acquisition and facility establishment. Chromosomes of varying lengths were used in the multiobjective optimization process. An important advantage of this is that multiple optimal solutions with different numbers of healthcare facilities can be compared directly. An a posteriori preference method was used in this study. TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) was applied to assess and compare the Pareto-optimal solutions and to select the best solution according to different weight vectors. Visualization of the best solution according to each weight vector and compromising among different objectives provided valuable possibilities for selection of the best alternative to decision makers.
An approach to improve the quality of the design hydraulic actuator by means of solving this problem as a multiobjective is suggested. A mathematical model of multiobjective optimization design and operating parameter...
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ISBN:
(纸本)9781467381147
An approach to improve the quality of the design hydraulic actuator by means of solving this problem as a multiobjective is suggested. A mathematical model of multiobjective optimization design and operating parameters of the hydraulic actuator is considered. All the set of Pareto-optimal alternatives is obtained for decision making in selection of the best variant of hydraulic actuator. The special geneticalgorithm for Pareto-set obtaining was developed.
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