This study proposes a fuzzy chance-constrained programming model to include uncertainty in the biogas supply chain design problem. Uncertain parameters of the model are available workforce, biomass demand, available b...
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This study proposes a fuzzy chance-constrained programming model to include uncertainty in the biogas supply chain design problem. Uncertain parameters of the model are available workforce, biomass demand, available biomass and biomass price. A hybrid solution framework consisting of Monte Carlo simulation and evolutionary algorithms (genetic algorithm and differential evolution) is put forward to find the exact and near global optimal solution for the fuzzy chance-constrained model. The results of the test problems show that evolutionary algorithms can effectively solve the mixed integer nonlinear model of biogas location allocation within a reasonable computational time. Also, validation of the hybrid solution framework at different confidence levels is verified. The impacts of uncertainty in available biomass, biomass demand and available workforce on the overall cost of biogas supply chain are studied through sensitivity analysis. A real-world case study with real-life data available from the Province of Khorasan Razavi is performed. This is the first study that designs a biogas supply chain for a province of Iran.
The increased use of composite materials and structures in many engineering applications led to the need for a more accurate analysis and design optimization. While methods of stress-strain analysis developed faster, ...
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The increased use of composite materials and structures in many engineering applications led to the need for a more accurate analysis and design optimization. While methods of stress-strain analysis developed faster, optimization techniques have been lagging behind. As a result, many designed structures do not fulfill their full potential. The present study demonstrates the major achievements in recent years in an application of evolutionary algorithms to the design optimization of fiber-reinforced laminated composite structures. Such structures are of much interest due to high structural design sensitivity to fiber orientations as well as complex multidimensional discrete optimization problems. Using an anisotropic multilayered cylindrical pressure vessel and an exact elasticity solution as an example, we show how the optimum, or near-optimum, solution can be found in a more efficient way.
Evaluating and comparing multi-objective optimizers is an important issue. But, when doing a comparison, it has to be noted that the results can be influenced highly by the selected Quality Indicator. Therefore, the i...
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Evaluating and comparing multi-objective optimizers is an important issue. But, when doing a comparison, it has to be noted that the results can be influenced highly by the selected Quality Indicator. Therefore, the impact of individual Quality Indicators on the ranking of Multi-objective Optimizers in the proposed method must be analyzed beforehand. In this paper the comparison of several different Quality Indicators with a method called Chess Rating System for evolutionary algorithms (CRS4EAs) was conducted in order to get a better insight on their characteristics and how they affect the ranking of Multi-objective evolutionary algorithms (MOEAs). Although it is expected that Quality Indicators with the same optimization goals would yield a similar ranking of MOEAs, it has been shown that results can be contradictory and significantly different. Consequently, revealing that claims about the superiority of one MOEA over another can be misleading. (c) 2017 Elsevier B.V. All rights reserved.
This paper presents an approach for improving proximity and diversity in multiobjective evolutionary algorithms (MOEAs). The idea is to discover new nondominated solutions in the promising area of search space. It can...
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This paper presents an approach for improving proximity and diversity in multiobjective evolutionary algorithms (MOEAs). The idea is to discover new nondominated solutions in the promising area of search space. It can be achieved by applying mutation only to the most converged and the least crowded individuals. In other words, the proximity and diversity can be improved because new nondominated solutions are found in the vicinity of the individuals highly converged and less crowded. Empirical results on multiobjective knapsack problems (MKPs) demonstrate that the proposed approach discovers a set of nondominated sokutions much closer to the global Pareto front while maintaining a better distribution of the solutions.
A brachistochrone is the path along which a weighted particle falls most quickly from one point to another, and a catenary is the smooth curve connecting two points whose surface of revolution has minimum area. Two ev...
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evolutionary algorithms appear as an interesting alternative to achieve minimal error rates and low numbers of rules in supervised learning tasks. In spite of the computational cost of this approach, some proposals ca...
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evolutionary algorithms appear as an interesting alternative to achieve minimal error rates and low numbers of rules in supervised learning tasks. In spite of the computational cost of this approach, some proposals can be applied to make the algorithm faster and more efficient. This paper describes some of these proposals, which are integrated in the evolutionary tool HIDER*. Specifically, we developed a new genetic encoding for the individuals of the evolutionary population and a novel data structure for the evaluation process. These approaches allow the evolutionary algorithms to reduce the high computational cost and to obtain high quality solutions.
This paper reproduces the performance of an international market capitalization shipping stock index and two physical shipping indexes by investing only in US stock portfolios. The index-tracking problem is addressed ...
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This paper reproduces the performance of an international market capitalization shipping stock index and two physical shipping indexes by investing only in US stock portfolios. The index-tracking problem is addressed using the differential evolution algorithm and the genetic algorithm. Portfolios are constructed by a subset of stocks picked from the shipping or the Dow Jones Composite Average indexes. To test the performance of the heuristics, three different trading scenarios are examined: annually, quarterly and monthly rebalancing, accounting for transaction costs where necessary. Competing portfolios are also assessed through predictive ability tests. Overall, the proposed investment strategies carry less risk compared to the tracked benchmark indexes while providing investors the opportunity to efficiently replicate the performance of both the stock and physical shipping indexes in the most cost-effective way. (C) 2012 Elsevier Ltd. All rights reserved.
A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers w...
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A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers, under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with the evolutionary algorithm outperform type-1 fuzzy controllers.
This paper considers a real-world two-dimensional strip packing problem involving specific machinery constraints and actual cutting production industry requirements. To adapt the problem to a wider range of machinery ...
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This paper considers a real-world two-dimensional strip packing problem involving specific machinery constraints and actual cutting production industry requirements. To adapt the problem to a wider range of machinery characteristics, the design objective considers the minimisation of material length and the total number of cuts for guillotinable-type patterns. The number of cuts required for the cutting process is crucial for the life of the industrial machines and is an important aspect in determining the cost and efficiency of the cutting operation. In this paper we propose the application of evolutionary algorithms to address the multi-objective problem, for which numerous approaches to its single-objective formulation exist, but for which multi-objective approaches are almost nonexistent. The multi-objective evolutionary algorithms applied provide a set of solutions offering a range of trade-offs between the two objectives from which clients can choose according to their needs. By considering both the length and number of cuts, they derive solutions with wastage levels similar to most previous approximations which just seek to optimise the overall length.
This editorial note presents the motivations, objectives, and structure of the special issue on scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems. In addi...
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This editorial note presents the motivations, objectives, and structure of the special issue on scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems. In addition, it provides the link to an associated Website where complementary material to the special issue is available.
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