This article presents a study which characterizes the computational efficiency behavior of a standard EA as a software program. The study analyzes the effects of some implementation decisions regarding memory utilizat...
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This paper tackles the problem of sizing a standalone hybrid photovoltaic-batteries-hydrogen (PV-hydrogen) system, by applying an evolutionary algorithm. The system is specifically designed to cover the power necessit...
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In the realm of fuzzy systems, interpretability is really appreciated in most applications, but it becomes essential in those cases in which an intensive human-machine interaction is necessary. Accuracy and interpreta...
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evolutionary algorithms (EAs) are bioinspired meta-heuristics that have been successfully used to solve multiobjective optimization problems (MOPs). However, when EAs need to perform several objective function evaluat...
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Multi-objective evolutionary algorithms (MOEAs) are currently a dynamic field of research that has attracted considerable attention. Mutation operators have been utilized by MOEAs as variation mechanisms. In particula...
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Multi-objective evolutionary algorithms (MOEAs) are currently a dynamic field of research that has attracted considerable attention. Mutation operators have been utilized by MOEAs as variation mechanisms. In particular, polynomial mutation (PLM) is one of the most popular variation mechanisms and has been utilized by many well-known MOEAs. In this paper, we revisit the PLM operator and we propose a fitness-guided version of the PLM. Experimental results obtained by non-dominated sorting genetic algorithm II and strength Pareto evolutionary algorithm 2 show that the proposed fitness-guided mutation operator outperforms the classical PLM operator, based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it.
Anaerobic digestion (AD) technology has become popular and is widely used due to its ability to produce renewable energy from wastes. The bioenergy produced in anaerobic digesters could be directly used as fuel, there...
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Anaerobic digestion (AD) technology has become popular and is widely used due to its ability to produce renewable energy from wastes. The bioenergy produced in anaerobic digesters could be directly used as fuel, thereby reducing the release of biogas to the atmosphere. Due to the limited knowledge on the different process disturbances and microbial composition that are vital for the efficient operation of AD systems, models and control strategies with respect to external influences are needed without wasting time and resources. Different simple and complex mechanistic and data-driven modeling approaches have been developed to describe the processes taking place in the AD system. Microbial activities have been incorporated in some of these models to serve as a predictive tool in biological processes. The flexibility and power of computational intelligence of evolutionary algorithms (EAs) as direct search algorithms to solve multiobjective problems and generate Pareto-optimal solutions have also been exploited. Thus, this paper reviews state-of-the-art models based on the computational optimization methods for renewable and sustainable energy optimization. This paper discusses the different types of model approaches to enhance AD processes for bioenergy generation. The optimization and control strategies using EAs for advanced reactor performance and biogas production are highlighted. This information would be of interest to a dynamic group of researchers, including microbiologists and process engineers, thereby offering the latest research advances and importance of AD technology in the production of renewable energy.
In this paper, an extension of the graph colouring problem is introduced to model a parallel machine scheduling problem with job incompatibility. To get closer to real-world applications, where the number of machines ...
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In this paper, an extension of the graph colouring problem is introduced to model a parallel machine scheduling problem with job incompatibility. To get closer to real-world applications, where the number of machines is limited and jobs have different processing times, each vertex of the graph requires multiple colours and the number of vertices with the same colour is bounded. In addition, several objectives related to scheduling are considered: makespan, number of pre-emptions and summation over the jobs' throughput times. Different solution methods are proposed, namely, two greedy heuristics, two tabu search methods and an adaptive memory algorithm. The latter uses multiple recombination operators, each one being designed for optimising a subset of objectives. The most appropriate operator is selected dynamically at each iteration, depending on its past performance. Experiments show that the proposed algorithm is effective and robust, while providing high-quality solutions on benchmark instances for the graph multi-colouring problem, a simplification of the considered problem.
In recent years sampling approaches have been used more widely than optimization algorithms to find parameters of conceptual rainfall-runoff models, but the difficulty of calibration of such models remains in dispute....
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In recent years sampling approaches have been used more widely than optimization algorithms to find parameters of conceptual rainfall-runoff models, but the difficulty of calibration of such models remains in dispute. The problem of finding a set of optimal parameters for conceptual rainfall-runoff models is interpreted differently in various studies, ranging from simple to relatively complex and difficult. In many papers, it is claimed that novel calibration approaches, so-called metaheuristics, outperform the older ones when applied to this task, but contradictory opinions are also plentiful. The present study aims at calibration of two simple lumped conceptual hydrological models, HBV and GR4J, by means of a large number of metaheuristic algorithms. The tests are performed on four catchments located in regions with relatively similar climatic conditions, but on different continents. The comparison shows that, although parameters found may somehow differ, the performance criteria achieved with simple lumped models calibrated by various metaheuristics are very similar and differences are insignificant from the hydrological point of view. However, occasionally some algorithms find slightly better solutions than those found by the vast majority of methods. This means that the problem of calibration of simple lumped HBV or GR4J models may be deceptive from the optimization perspective, as the vast majority of algorithms that follow a common evolutionary principle of survival of the fittest lead to sub-optimal solutions.
The various flavors of evolutionary algorithms look very similar when cleared of algorithmically irrelevant differences such as domain of application and phenotype interpretation. Representation-independent algorithmi...
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ISBN:
(纸本)9781450306904
The various flavors of evolutionary algorithms look very similar when cleared of algorithmically irrelevant differences such as domain of application and phenotype interpretation. Representation-independent algorithmic characteristics like the selection scheme can be freely exchanged between algorithms. Ultimately, the origin of the differences of the various flavors of evolutionary algorithms is rooted in the solution representation and relative genetic operators. Are these differences only superficial? Is there a deeper unity encompassing all evolutionary algorithms beyond the specific representation? Is a general mathematical framework unifying search operators for all solution representations at all possible? The aim of the tutorial is to introduce a formal, but intuitive, unified point of view on evolutionary algorithms across representations based on geometric ideas, which provides a possible answer to the above questions. It also presents the benefits for both theory and practice brought by this novel perspective. The key idea behind the geometric framework is that search operators have a dual nature. The same search operator can be defined (i) on the underlying solution representations and, equivalently, (ii) on the structure of the search space by means of simple geometric shapes, like balls and segments. These shapes are used to delimit the region of space that includes all possible offspring with respect to the location of their parents. The geometric definition of a search operator is of interest because it can be applied - unchanged - to different search spaces associated with different representations. This, in effect, allows us to define exactly the same search operator across representations in a rigorous way. The geometric view on search operators has a number of interesting consequences of which this tutorial will give a comprehensive overview. These include (i) a straightforward view on the fitness landscape seen by recombination operators, (ii) a
The wire electro-discharge machining technique is used in many operations, from the simplest cutting applications to the manufacturing of complex and delicate parts. Costs and the variety of wire used in the cutting p...
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The wire electro-discharge machining technique is used in many operations, from the simplest cutting applications to the manufacturing of complex and delicate parts. Costs and the variety of wire used in the cutting process vary according to the particular workpiece to be cut. The literature on this subject features studies conducted on the surface roughness and the metal removal rate. However, the surface sensitivity in the manufacturing of cutting dies is not a crucial property. The most important variable, rather, is the cost involved in making simple cutting dies. In this study, a Bohler K100 workpiece and CuZn37 wire material has been used to find the optimal conditions for high quality surface roughness, maximizing metal removal rate and minimizing wire consumption. Furthermore, the metal removal rate related directly to the cutting speed was calculated and compared with the consumption. To facilitate calculation of wire consumption, the evolutionary programming module was used for modeling and derivation of the formula for calculation with 99 % accuracy.
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