Multi-energy systems (MES) allow various energy forms, such as electricity, gas, and heat, to interact achieve transfer mutually benefit, reducing the probability of load cutting in event a failure, increasing utilization efficiency, improving reliability robustness overall supply system. Since storage can help restore power case failure store surplus enhance flexibility MES, this work provides...

Abstract Many real-world problems can be naturally formulated as discrete multi-objective optimisation (DMOO) problems. We have proposed a novel Physarum-inspired competition algorithm (PCA) to tackle these DMOO Our is based on hexagonal cellular automata (CA) representation of problem search space and reaction–diffusion systems that control the Physarum motility. Physarum’s decision-making pow...

Hyper-heuristics are emerging methodologies that perform a search over the space of heuristics to solve difficult computational optimization problems. There are two main types of hyper-heuristics: selective and generative hyper-heuristics. An online selective hyper-heuristic framework manages a set of low level heuristics and aims to choose the best one at any given time using a performance mea...

Most problems in search-based software engineering involves balancing conflicting objectives. Prior approaches to this task have required a large number of evaluations– making them very slow to execute and very hard to comprehend. To solve these problems, this paper introduces FLASH, a decisiontree based optimizer that incrementally grows one decision tree per objective. These trees are then us...

The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

Streptococcus pyogenes strains producing pyrogenic exotoxin A (scarlet fever toxin) have recently caused episodes of streptococcal toxic-shock-like syndrome (TSLS). We exploited knowledge of genetic diversity and relationships among exotoxin A-producing patient strains provided by multilocus enzyme electrophoresis to select strains for comparative sequencing of toxin genes. Our analysis identif...

Multi-objective optimization problems arise frequently in applications, but can often only be solved approximately by heuristic approaches. Evolutionary algorithms have been widely used to tackle multi-objective problems. These algorithms use different measures to ensure diversity in the objective space but are not guided by a formal notion of approximation. We present a framework for evolution...

In our previous work [1], it has been shown that the performance of multi-objective evolutionary algorithms can be greatly enhanced if the regularity in the distribution of Pareto-optimal solutions is used. This paper suggests a new hybrid multi-objective evolutionary algorithm by introducing a convergence based criterion to determine when the modelbased method and when the genetics-based metho...

We would like to thank Jasper Vrugt for his comment on our recent paper Tang et al. (2006) in which we compare the Strength Pareto Evolutionary Algorithm 2 (SPEA2), the Multi-objective Shuffled Complex Evolution Metropolis algorithm (MOSCEM-UA), and the Epsilon Dominance Nondominated Sorted Genetic Algorithm II (ε-NSGAII) using a statistical metrics-based approach. To frame our response, we wil...

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.12.042 ⇑ Corresponding author. Tel.: +86 571 87952598; fa E-mail address: [email protected] (H. Zho Combustion optimization has been proved to be an effective way to reduce the NOx emissions and unburned carbon in fly ash by carefully setting the operational parameters of boilers. However, there is a trade-off relat...